mcp-bcrp

Instructions

Implementation Reference

• mcp_bcrp/server.py:92-107 (handler)

  The MCP tool registration for `search_series` which delegates to the `_search_series` function.

  @mcp.tool()
  async def search_series(query: str) -> str:
      """
      Search for BCRP economic indicators by keyword.
      
      Uses deterministic search with fuzzy matching. Returns the best match
      or an ambiguity error if multiple matches are equally scored.
      
      Args:
          query: Search term (e.g., "tipo de cambio", "inflacion", "PBI")
      
      Returns:
          JSON string with match result containing codigo_serie and confidence,
          or error details if ambiguous or not found.
      """
      return await _search_series(query)

• mcp_bcrp/server.py:21-50 (handler)

  The core implementation logic of the search functionality used by the `search_series` tool.

  async def _search_series(query: str) -> str:
      """
      Uses robust local metadata search.
      Now returns deterministic result via SearchEngine.solve().
      """
      try:
          await metadata_client.load()
          
          logger.info(f"Searching for: {query}")
          
          # First try deterministic solve
          result = metadata_client.solve(query)
          
          if "error" not in result:
              # Success - return JSON with the match
              return json.dumps(result, ensure_ascii=False)
          
          if result.get("error") == "ambiguedad":
              # Return ambiguity info for user to refine
              return json.dumps(result, ensure_ascii=False)
          
          # Fallback to fuzzy search for exploratory queries
          df = metadata_client.search(query)
          
          if df.empty:
              return "No series found matching that query."
          return df.to_json(orient='records')
      except Exception as e:
          logger.error(f"Search failed: {e}")
          return f"Search failed: {str(e)}"