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