forked from Rockachopa/Timmy-time-dashboard
## 1. MCP (Model Context Protocol) Implementation ### Registry (src/mcp/registry.py) - Tool registration with JSON schemas - Dynamic tool discovery - Health tracking per tool - Metrics collection (latency, error rates) - @register_tool decorator for easy registration ### Server (src/mcp/server.py) - MCPServer class implementing MCP protocol - MCPHTTPServer for FastAPI integration - Standard endpoints: list_tools, call_tool, get_schema ### Schemas (src/mcp/schemas/base.py) - create_tool_schema() helper - Common parameter types - Standard return types ### Bootstrap (src/mcp/bootstrap.py) - Automatic tool module loading - Status reporting ## 2. MCP-Compliant Tools (src/tools/) | Tool | Purpose | Category | |------|---------|----------| | web_search | DuckDuckGo search | research | | read_file | File reading | files | | write_file | File writing (confirmation) | files | | list_directory | Directory listing | files | | python | Python code execution | code | | memory_search | Vector memory search | memory | All tools have proper schemas, error handling, and MCP registration. ## 3. Event Bus (src/events/bus.py) - Async publish/subscribe pattern - Pattern matching with wildcards (agent.task.*) - Event history tracking - Concurrent handler execution - Module-level singleton for system-wide use ## 4. Sub-Agents (src/agents/) All agents inherit from BaseAgent with: - Agno Agent integration - MCP tool registry access - Event bus connectivity - Structured logging ### Agent Roster | Agent | Role | Tools | Purpose | |-------|------|-------|---------| | Seer | Research | web_search, read_file, memory_search | Information gathering | | Forge | Code | python, write_file, read_file | Code generation | | Quill | Writing | write_file, read_file, memory_search | Content creation | | Echo | Memory | memory_search, read_file, write_file | Context retrieval | | Helm | Routing | memory_search | Task routing decisions | | Timmy | Orchestrator | All tools | Coordination & user interface | ### Timmy Orchestrator - Analyzes user requests - Routes to appropriate sub-agent - Handles direct queries - Manages swarm coordination - create_timmy_swarm() factory function ## 5. Integration All components wired together: - Tools auto-register on import - Agents connect to event bus - MCP server provides HTTP API - Ready for dashboard integration ## Tests - All 973 existing tests pass - New components tested manually - Import verification successful Next steps: Cascade Router, Self-Upgrade Loop, Dashboard integration
125 lines
3.5 KiB
Python
125 lines
3.5 KiB
Python
"""Code execution tool.
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MCP-compliant tool for executing Python code.
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"""
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import logging
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import traceback
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from typing import Any
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from mcp.registry import register_tool
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from mcp.schemas.base import create_tool_schema, PARAM_STRING, PARAM_BOOLEAN, RETURN_STRING
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logger = logging.getLogger(__name__)
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PYTHON_SCHEMA = create_tool_schema(
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name="python",
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description="Execute Python code. Use for calculations, data processing, or when precise computation is needed. Code runs in a restricted environment.",
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parameters={
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"code": {
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**PARAM_STRING,
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"description": "Python code to execute",
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},
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"return_output": {
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**PARAM_BOOLEAN,
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"description": "Return the value of the last expression",
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"default": True,
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},
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},
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required=["code"],
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returns=RETURN_STRING,
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)
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def python(code: str, return_output: bool = True) -> str:
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"""Execute Python code in restricted environment.
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Args:
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code: Python code to execute
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return_output: Whether to return last expression value
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Returns:
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Execution result or error message
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"""
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# Safe globals for code execution
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safe_globals = {
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"__builtins__": {
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"abs": abs,
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"all": all,
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"any": any,
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"bin": bin,
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"bool": bool,
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"dict": dict,
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"enumerate": enumerate,
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"filter": filter,
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"float": float,
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"format": format,
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"hex": hex,
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"int": int,
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"isinstance": isinstance,
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"issubclass": issubclass,
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"len": len,
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"list": list,
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"map": map,
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"max": max,
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"min": min,
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"next": next,
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"oct": oct,
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"ord": ord,
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"pow": pow,
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"print": lambda *args, **kwargs: None, # Disabled
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"range": range,
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"repr": repr,
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"reversed": reversed,
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"round": round,
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"set": set,
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"slice": slice,
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"sorted": sorted,
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"str": str,
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"sum": sum,
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"tuple": tuple,
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"type": type,
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"zip": zip,
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}
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}
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# Allowed modules
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allowed_modules = ["math", "random", "statistics", "datetime", "json"]
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for mod_name in allowed_modules:
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try:
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safe_globals[mod_name] = __import__(mod_name)
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except ImportError:
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pass
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try:
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# Compile and execute
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compiled = compile(code, "<string>", "eval" if return_output else "exec")
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if return_output:
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result = eval(compiled, safe_globals, {})
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return f"Result: {result}"
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else:
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exec(compiled, safe_globals, {})
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return "Code executed successfully."
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except SyntaxError:
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# Try as exec if eval fails
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try:
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compiled = compile(code, "<string>", "exec")
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exec(compiled, safe_globals, {})
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return "Code executed successfully."
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except Exception as exc:
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error_msg = traceback.format_exc()
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logger.error("Python execution failed: %s", exc)
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return f"Error: {exc}\n\n{error_msg}"
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except Exception as exc:
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error_msg = traceback.format_exc()
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logger.error("Python execution failed: %s", exc)
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return f"Error: {exc}\n\n{error_msg}"
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# Register with MCP
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register_tool(name="python", schema=PYTHON_SCHEMA, category="code")(python)
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