"CrewAI" matching MCP servers:

DingDawg Loop Protocol (DDLP) — safe scheduled AI agents with governance gates. Every loop execution is verified, receipted, and fail-closed. MCP-native, works with CrewAI, LangGraph, Claude Code, Cursor.

Enables natural-language analysis of insurance customer migration data through CrewAI agents, providing tools for querying renewals, churn, competitor returns, and feature adoption.

A lightweight Python-based server designed to run, manage and create CrewAI workflows using the Model Context Protocol for communicating with LLMs and tools like Claude Desktop or Cursor IDE.

Enables agents and MCP-compliant clients to run multi-language code in a deterministic, zero-dependency sandbox where AST security analysis blocks dangerous syscalls and isolated execution telemetry is captured. It exposes this through JSON-RPC 2.0 stdio, letting frameworks like LangGraph, CrewAI, Cursor, and Claude Desktop validate and execute agent-generated code safely.

Enables agents and MCP-compliant clients to resolve tool execution graphs as topological dependency DAGs, batching independent calls in parallel and speculatively prefetching arguments to cut latency and token burn. Runs deterministically as a zero-dependency JSON-RPC 2.0 stdio server for frameworks like LangGraph, CrewAI, AutoGen, and IDEs such as Cursor, Windsurf, and Claude Desktop.