Elrond MCP

Instructions

Implementation Reference

• elrond_mcp/server.py:25-64 (handler)

  The primary MCP tool handler for 'consult_the_council'. Decorated with @app.tool() for registration, performs input validation, creates CritiqueRequest, and delegates to process_proposal for core logic execution.
  @app.tool() async def consult_the_council(proposal: str) -> ThinkingAugmentationResult: """ Analyze a proposal using hierarchical LLM critique and synthesis. This tool runs three specialized critique agents (positive, neutral, negative) in parallel to analyze the proposal, then synthesizes their perspectives into a comprehensive analysis with recommendations. Args: proposal: Markdown-formatted proposal outlining the salient points of the solution to be analyzed Returns: Complete analysis including all critiques and synthesis with consensus view, recommendations, and next steps """ try: logger.info("Received thinking augmentation request") # Validate input if not proposal.strip(): raise ValueError("Proposal cannot be empty") if len(proposal.strip()) < 10: raise ValueError("Proposal must be at least 10 characters long") # Create request object and process request = CritiqueRequest(proposal=proposal) result = await process_proposal(request) logger.info("Thinking augmentation completed successfully") return result except ValueError as e: logger.error(f"Validation error: {e}") raise except Exception as e: logger.error(f"Error in thinking augmentation: {e}") raise RuntimeError(f"Failed to process proposal: {str(e)}") from e
• elrond_mcp/models.py:139-161 (schema)

  Pydantic BaseModel defining the structured output schema returned by the tool, including original proposal, three critiques, synthesis, and processing metadata.
  class ThinkingAugmentationResult(BaseModel): """Complete result from the thinking augmentation process.""" original_proposal: str = Field( ..., description="The original proposal that was analyzed" ) critiques: list[CritiqueResponse] = Field( ..., description="All critique responses (positive, neutral, negative)", min_length=3, max_length=3, ) synthesis: SynthesisResponse = Field( ..., description="Final synthesis of all perspectives" ) processing_metadata: dict = Field( default_factory=dict, description="Metadata about the processing (timestamps, model versions, etc.)", )
• elrond_mcp/agents.py:221-275 (helper)

  Core helper function implementing the full thinking augmentation pipeline: creates three parallel CritiqueAgents, gathers their responses, synthesizes with SynthesisAgent, and constructs the final result.
  async def process_proposal(request: CritiqueRequest) -> ThinkingAugmentationResult: """Process a proposal through the complete thinking augmentation pipeline.""" start_time = datetime.now(UTC) try: logger.info("Starting thinking augmentation process") # Create agents for this processing request positive_agent = CritiqueAgent("positive") neutral_agent = CritiqueAgent("neutral") negative_agent = CritiqueAgent("negative") synthesis_agent = SynthesisAgent() # Run all critiques in parallel critique_tasks = [ positive_agent.analyze_proposal(request.proposal), neutral_agent.analyze_proposal(request.proposal), negative_agent.analyze_proposal(request.proposal), ] logger.info("Running parallel critiques") critiques = await asyncio.gather(*critique_tasks) logger.info("Critiques completed, starting synthesis") # Synthesize all critiques synthesis = await synthesis_agent.synthesize_critiques( request.proposal, critiques ) end_time = datetime.now(UTC) processing_time = (end_time - start_time).total_seconds() logger.info(f"Thinking augmentation completed in {processing_time:.2f} seconds") # Create final result result = ThinkingAugmentationResult( original_proposal=request.proposal, critiques=critiques, synthesis=synthesis, processing_metadata={ "start_time": start_time.isoformat(), "end_time": end_time.isoformat(), "processing_time_seconds": processing_time, "critique_model": "gemini-2.5-flash", "synthesis_model": "gemini-2.5-pro", "num_critiques": len(critiques), }, ) return result except Exception as e: logger.error(f"Error in thinking augmentation process: {e}") raise
• elrond_mcp/models.py:16-24 (schema)

  Pydantic model used internally to wrap the tool input 'proposal' string with validation.
  class CritiqueRequest(BaseModel): """Request model for critique analysis.""" proposal: str = Field( ..., description="Markdown-formatted proposal outlining the salient points of the " "solution", min_length=10, )
• elrond_mcp/server.py:25-25 (registration)

  The @app.tool() decorator registers the consult_the_council function as an MCP tool.
  @app.tool()