404 lines
19 KiB
Python
404 lines
19 KiB
Python
"""MCP client-side handlers for server-initiated requests: sampling
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(sampling/createMessage, text and tool-use results) and elicitation."""
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import asyncio
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import json
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import logging
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import time
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from typing import Callable, List, Optional
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from tools.mcp_tool_common import _MISSING, _exc_str, _safe_numeric, _sanitize_error, mcp_field, _core
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from tools.mcp_tool_schema import _normalize_mcp_input_schema
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logger = logging.getLogger("tools.mcp_tool")
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def _tool_use_id(block):
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"""Tool-use id (the discriminator for a tool *result* block), read under both
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SDK spellings — on mcp 2.x a bare ``hasattr(b, "toolUseId")`` is False and
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would silently drop tool results."""
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return mcp_field(block, "tool_use_id", "toolUseId", _MISSING)
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def _is_tool_use(block) -> bool:
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return hasattr(block, "name") and hasattr(block, "input")
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def _tool_result_text(block) -> str:
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"""Text of a ToolResultContent block ("" when it carries no content)."""
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content = getattr(block, "content", None)
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if content is None:
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return ""
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items = content if isinstance(content, list) else [content]
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return "\n".join(item.text for item in items if hasattr(item, "text"))
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def _content_part(block) -> Optional[dict]:
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"""One OpenAI content part for a text/image block; None when unsupported."""
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if hasattr(block, "text"):
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return {"type": "text", "text": block.text}
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mime = mcp_field(block, "mime_type", "mimeType", _MISSING)
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if hasattr(block, "data") and mime is not _MISSING:
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return {"type": "image_url", "image_url": {"url": f"data:{mime};base64,{block.data}"}}
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logger.warning("Unsupported sampling content block type: %s (skipped)", type(block).__name__)
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return None
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def _tool_call_dict(tu, index: int) -> dict:
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args = tu.input
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return {
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"id": getattr(tu, "id", f"call_{index}"),
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"type": "function",
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"function": {
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"name": tu.name,
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"arguments": json.dumps(args, ensure_ascii=False) if isinstance(args, dict) else str(args),
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},
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}
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def _convert_sampling_message(msg) -> List[dict]:
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"""One MCP SamplingMessage -> OpenAI-format messages (tool results first,
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then either an assistant tool_calls message or plain content)."""
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blocks = msg.content_as_list if hasattr(msg, "content_as_list") else (
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msg.content if isinstance(msg.content, list) else [msg.content]
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)
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tool_results = [b for b in blocks if _tool_use_id(b) is not _MISSING]
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tool_uses = [b for b in blocks if _is_tool_use(b) and _tool_use_id(b) is _MISSING]
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content_blocks = [b for b in blocks if _tool_use_id(b) is _MISSING and not _is_tool_use(b)]
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out = [{"role": "tool", "tool_call_id": _tool_use_id(tr), "content": _tool_result_text(tr)} for tr in tool_results]
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if tool_uses:
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msg_dict: dict = {"role": msg.role, "tool_calls": [_tool_call_dict(tu, i) for i, tu in enumerate(tool_uses)]}
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text_parts = [b.text for b in content_blocks if hasattr(b, "text")]
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if text_parts:
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msg_dict["content"] = "\n".join(text_parts)
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out.append(msg_dict)
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elif content_blocks:
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if len(content_blocks) == 1 and hasattr(content_blocks[0], "text"):
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out.append({"role": msg.role, "content": content_blocks[0].text})
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else:
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parts = [p for p in map(_content_part, content_blocks) if p is not None]
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if parts:
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out.append({"role": msg.role, "content": parts})
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return out
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def _parse_tool_call_arguments(server_name: str, args) -> dict:
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"""LLM tool_calls arguments -> dict; malformed JSON / non-dict values are
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wrapped as ``{"_raw": ...}`` rather than dropped."""
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if isinstance(args, str):
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try:
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return json.loads(args)
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except (json.JSONDecodeError, ValueError):
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logger.warning(
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"MCP server '%s': malformed tool_calls arguments from LLM (wrapping as raw): %.100s",
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server_name, args,
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)
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return {"_raw": args}
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return args if isinstance(args, dict) else {"_raw": str(args)}
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def _response_total_tokens(response, default):
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return getattr(getattr(response, "usage", None), "total_tokens", default)
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class SamplingHandler:
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"""Handles sampling/createMessage requests for one MCP server; passed to
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``ClientSession`` as ``sampling_callback``. All state (rate-limit
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timestamps, metrics, tool-loop counter) is per instance. Runs on the MCP
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background loop; the sync LLM call is offloaded via ``asyncio.to_thread``.
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Deprecated upstream (MCP 2026-07-28, SEP-2577, 12-month window): stays fully
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functional because handshake-era servers still issue it, but do NOT grow new
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capability here — modern servers use MRTR, handled by the SDK session layer.
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"""
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_STOP_REASON_MAP = {"stop": "endTurn", "length": "maxTokens", "tool_calls": "toolUse"}
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_LOG_LEVELS = {"debug": logging.DEBUG, "info": logging.INFO, "warning": logging.WARNING}
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def __init__(self, server_name: str, config: dict):
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self.server_name = server_name
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self.max_rpm = _safe_numeric(config.get("max_rpm", 10), 10, int)
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self.timeout = _safe_numeric(config.get("timeout", 30), 30, float)
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self.max_tokens_cap = _safe_numeric(config.get("max_tokens_cap", 4096), 4096, int)
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self.max_tool_rounds = _safe_numeric(config.get("max_tool_rounds", 5), 5, int, minimum=0)
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self.model_override = config.get("model")
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self.allowed_models = config.get("allowed_models", [])
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self.audit_level = self._LOG_LEVELS.get(str(config.get("log_level", "info")).lower(), logging.INFO)
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self._rate_timestamps: List[float] = []
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self._tool_loop_count = 0
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self.metrics = {"requests": 0, "errors": 0, "tokens_used": 0, "tool_use_count": 0}
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def _check_rate_limit(self) -> bool:
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"""Sliding-window (60s) limiter; True if the request is allowed."""
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now = time.time()
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self._rate_timestamps[:] = [t for t in self._rate_timestamps if t > now - 60]
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if len(self._rate_timestamps) >= self.max_rpm:
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return False
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self._rate_timestamps.append(now)
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return True
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def _resolve_model(self, preferences) -> Optional[str]:
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"""Config override > server hint > None (use default)."""
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if self.model_override:
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return self.model_override
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for hint in (getattr(preferences, "hints", None) or []):
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if getattr(hint, "name", None):
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return hint.name
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return None
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def _convert_messages(self, params) -> List[dict]:
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"""Convert MCP SamplingMessages to OpenAI format (``content_as_list``
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when the SDK provides it; per-block duck-typed dispatch)."""
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return [m for msg in params.messages for m in _convert_sampling_message(msg)]
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@staticmethod
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def _error(message: str, code: int = -1):
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"""Return ErrorData (MCP spec) or raise as fallback."""
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if _core._MCP_SAMPLING_TYPES:
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return _core.ErrorData(code=code, message=message)
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raise Exception(message)
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def _fail(self, message: str):
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"""Count an error and return the ErrorData for it."""
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self.metrics["errors"] += 1
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return self._error(message)
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def _log_response(self, response, suffix: str = "", *args) -> None:
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logger.log(
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self.audit_level, "MCP server '%s' sampling response: model=%s, tokens=%s" + suffix,
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self.server_name, response.model, _response_total_tokens(response, "?"), *args,
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)
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def _build_tool_use_result(self, choice, response):
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"""Build a CreateMessageResultWithTools from an LLM tool_calls response,
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subject to tool-loop governance (``max_tool_rounds``; 0 disables)."""
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self.metrics["tool_use_count"] += 1
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if self.max_tool_rounds == 0:
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self._tool_loop_count = 0
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return self._error(f"Tool loops disabled for server '{self.server_name}' (max_tool_rounds=0)")
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self._tool_loop_count += 1
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if self._tool_loop_count > self.max_tool_rounds:
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self._tool_loop_count = 0
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return self._error(
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f"Tool loop limit exceeded for server '{self.server_name}' (max {self.max_tool_rounds} rounds)"
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)
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content_blocks = [
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_core.ToolUseContent(
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type="tool_use", id=tc.id, name=tc.function.name,
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input=_parse_tool_call_arguments(self.server_name, tc.function.arguments),
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)
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for tc in choice.message.tool_calls
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]
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self._log_response(response, ", tool_calls=%d", len(content_blocks))
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return _core.CreateMessageResultWithTools(
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role="assistant", content=content_blocks, model=response.model, stopReason="toolUse",
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)
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def _build_text_result(self, choice, response):
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"""Build a CreateMessageResult from a normal text response (resets the tool loop)."""
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self._tool_loop_count = 0
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self._log_response(response)
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return _core.CreateMessageResult(
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role="assistant",
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content=_core.TextContent(type="text", text=_sanitize_error(choice.message.content or "")),
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model=response.model,
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stopReason=self._STOP_REASON_MAP.get(choice.finish_reason, "endTurn"),
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)
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def session_kwargs(self) -> dict:
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"""Kwargs to pass to ClientSession for sampling support."""
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return {
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"sampling_callback": self,
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"sampling_capabilities": _core.SamplingCapability(tools=_core.SamplingToolsCapability()),
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}
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def _admit(self, params):
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"""Rate-limit + allowed_models gate. Returns ``(resolved_model, None)``
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or ``(None, ErrorData)``."""
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if not self._check_rate_limit():
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logger.warning("MCP server '%s' sampling rate limit exceeded (%d/min)", self.server_name, self.max_rpm)
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return None, self._fail(
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f"Sampling rate limit exceeded for server '{self.server_name}' ({self.max_rpm} requests/minute)"
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)
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model = self._resolve_model(mcp_field(params, "model_preferences", "modelPreferences"))
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resolved_model = model or self.model_override or ""
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if self.allowed_models and resolved_model and resolved_model not in self.allowed_models:
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logger.warning(
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"MCP server '%s' requested model '%s' not in allowed_models", self.server_name, resolved_model,
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)
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return None, self._fail(
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f"Model '{resolved_model}' not allowed for server "
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f"'{self.server_name}'. Allowed: {', '.join(self.allowed_models)}"
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)
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return resolved_model, None
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def _build_llm_call(self, params, resolved_model: str) -> Callable[[], object]:
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"""Translate the sampling params into a zero-arg sync ``call_llm`` thunk
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(run off-loop so the MCP loop is not blocked)."""
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from agent.auxiliary_client import call_llm
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messages = self._convert_messages(params)
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system_prompt = mcp_field(params, "system_prompt", "systemPrompt")
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if system_prompt:
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messages.insert(0, {"role": "system", "content": system_prompt})
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max_tokens = min(mcp_field(params, "max_tokens", "maxTokens", self.max_tokens_cap), self.max_tokens_cap)
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temperature = getattr(params, "temperature", None)
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# Forward server-provided tools.
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server_tools = getattr(params, "tools", None)
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tools = [
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{
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"type": "function",
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"function": {
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"name": getattr(t, "name", ""),
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"description": getattr(t, "description", "") or "",
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"parameters": _normalize_mcp_input_schema(mcp_field(t, "input_schema", "inputSchema")),
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},
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}
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for t in server_tools
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] if server_tools else None
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logger.log(
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self.audit_level,
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"MCP server '%s' sampling request: model=%s, max_tokens=%d, messages=%d",
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self.server_name, resolved_model, max_tokens, len(messages),
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)
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return lambda: call_llm(
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task="mcp", model=resolved_model or None, messages=messages, temperature=temperature,
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max_tokens=max_tokens, tools=tools, timeout=self.timeout,
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)
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async def __call__(self, context, params):
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"""SDK sampling callback (``SamplingFnT``). Returns CreateMessageResult,
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CreateMessageResultWithTools, or ErrorData."""
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resolved_model, err = self._admit(params)
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if err is not None:
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return err
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sync_call = self._build_llm_call(params, resolved_model)
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try:
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response = await asyncio.wait_for(asyncio.to_thread(sync_call), timeout=self.timeout)
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except asyncio.TimeoutError:
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return self._fail(f"Sampling LLM call timed out after {self.timeout}s for server '{self.server_name}'")
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except Exception as exc:
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return self._fail(f"Sampling LLM call failed: {_sanitize_error(_exc_str(exc))}")
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# Empty choices happen on content filtering / provider errors.
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if not getattr(response, "choices", None):
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return self._fail(f"LLM returned empty response (no choices) for server '{self.server_name}'")
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choice = response.choices[0]
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self.metrics["requests"] += 1
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total_tokens = _response_total_tokens(response, 0)
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if isinstance(total_tokens, int):
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self.metrics["tokens_used"] += total_tokens
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if choice.finish_reason == "tool_calls" and getattr(choice.message, "tool_calls", None):
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return self._build_tool_use_result(choice, response)
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return self._build_text_result(choice, response)
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def _format_elicitation_schema_summary(schema: dict, server_name: str) -> str:
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"""Render a flat-object requested_schema as a human-readable field list
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(names, types, descriptions) so the user knows what they're approving."""
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props = schema.get("properties") if isinstance(schema, dict) else None
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if not isinstance(props, dict) or not props:
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return f"Approval requested by MCP server '{server_name}'."
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lines = [f"Fields requested by MCP server '{server_name}':"]
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for field_name, field_spec in props.items():
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spec = field_spec if isinstance(field_spec, dict) else {}
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field_type = str(spec.get("type", "") or "")
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field_desc = str(spec.get("description", "") or "")
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suffix = f" ({field_type})" if field_type else ""
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lines.append(f" - {field_name}{suffix}: {field_desc}" if field_desc else f" - {field_name}{suffix}")
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return "\n".join(lines)
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class ElicitationHandler:
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"""Handles ``elicitation/create`` requests for one MCP server; passed to
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``ClientSession`` as ``elicitation_callback``. Form-mode requests route
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through Hermes' approval system (CLI, TUI, Telegram, ...); URL-mode is
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declined as unsupported. Fail-closed: any timeout, exception or unexpected
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state returns decline/cancel, never a silent accept."""
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# asyncio-side safety net over the approval's own input() timeout so the
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# MCP loop never blocks indefinitely if the inner timeout is bypassed.
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_OUTER_TIMEOUT_GRACE_SECONDS = 5
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# consent answer -> (ElicitResult action, metric); anything else declines.
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_ANSWER_RESULTS = {"accept": ("accept", "accepted"), "cancel": ("cancel", "errors")}
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def __init__(self, server_name: str, config: dict, owner: Optional["MCPServerTask"] = None):
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self.server_name = server_name
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# Default 5 min mirrors the gateway approval default so async surfaces
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# (Telegram, Slack) have time to respond.
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self.timeout = _safe_numeric(config.get("timeout", 300), 300, float)
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# Back-reference for the agent's contextvars snapshot; optional so the
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# handler stays unit-testable in isolation.
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self.owner = owner
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self.metrics = {"requests": 0, "accepted": 0, "declined": 0, "errors": 0}
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def session_kwargs(self) -> dict:
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"""Kwargs to pass to ClientSession for elicitation support."""
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return {"elicitation_callback": self}
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def _result(self, action: str, metric: str):
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"""Count *metric* and return ``ElicitResult(action)`` (accept carries empty content)."""
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self.metrics[metric] += 1
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if action == "accept":
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return _core.ElicitResult(action="accept", content={})
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return _core.ElicitResult(action=action)
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def _consent_thunk(self, message: str, description: str) -> Callable[[], str]:
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"""Sync consent call, replaying the agent's contextvars snapshot when the
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owner captured one: the recv-loop task does NOT inherit them, and
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gateway-platform detection needs them. ``Context.run`` executes a
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context once, so it is copied per elicitation."""
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from tools.approval import request_elicitation_consent
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kwargs = {"timeout_seconds": int(self.timeout), "surface": f"mcp-elicitation/{self.server_name}"}
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captured = getattr(self.owner, "_pending_call_context", None) if self.owner else None
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if captured is None:
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return lambda: request_elicitation_consent(message, description, **kwargs)
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return lambda: captured.copy().run(request_elicitation_consent, message, description, **kwargs)
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async def __call__(self, context, params):
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"""SDK elicitation callback (``ElicitationFnT``). Returns ElicitResult or ErrorData."""
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self.metrics["requests"] += 1
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# URL-mode (OAuth, payment) would need a browser + waiting for
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# notifications/elicitation/complete — not implemented; decline cleanly.
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if getattr(params, "mode", "form") == "url":
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logger.info(
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"MCP server '%s' requested URL-mode elicitation; declining (URL-mode elicitation not implemented)",
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self.server_name,
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)
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return self._result("decline", "declined")
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message = getattr(params, "message", "") or f"MCP server '{self.server_name}' is requesting your approval"
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# ``requestedSchema`` on mcp 1.x, ``requested_schema`` on 2.0 (pydantic
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# aliases don't apply to attribute access) — read both or the user is
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# asked to approve without seeing which fields the server wants.
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schema = getattr(params, "requestedSchema", None) or getattr(params, "requested_schema", None) or {}
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description = _format_elicitation_schema_summary(schema, self.server_name)
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logger.info("MCP server '%s' elicitation request: %s", self.server_name, _sanitize_error(message)[:200])
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# Lazy import avoids import-order coupling with early-bootstrap tools.approval.
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try:
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invoke_consent = self._consent_thunk(message, description)
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except Exception as exc: # pragma: no cover -- defensive
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logger.error("MCP server '%s' elicitation: approval system unavailable: %s", self.server_name, exc)
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return self._result("decline", "errors")
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# Offload the sync consent flow to a thread — inline it would freeze the
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# MCP loop and every other RPC on this session.
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try:
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answer = await asyncio.wait_for(
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asyncio.to_thread(invoke_consent), timeout=self.timeout + self._OUTER_TIMEOUT_GRACE_SECONDS,
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)
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except asyncio.TimeoutError:
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logger.warning("MCP server '%s' elicitation timed out after %ds", self.server_name, int(self.timeout))
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return self._result("cancel", "errors")
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except Exception as exc:
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logger.error("MCP server '%s' elicitation failed: %s", self.server_name, exc, exc_info=True)
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return self._result("decline", "errors")
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return self._result(*self._ANSWER_RESULTS.get(answer, ("decline", "declined")))
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