"Searching for local information or documents" matching MCP servers:

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Create sandboxed local development environments directly from Github and execute tests, see coverage and more! Supports Python, Node, Bun and many test runners.

Secure agent coding runtime for local Git repos with policy enforcement, RBAC, sessions, approval workflow, and sandboxed writes, optionally connectable to ChatGPT via Secure MCP Tunnel.

A local, zero-dependency MCP server that cuts coding-agent round-trips by aggregating search, read, edit, exec, git, and savings tools into single, validated calls, with cost tracking and no data leaving the machine.

A Windows proof-of-concept MCP server that connects ChatGPT developer-mode to a local Codex CLI via Secure MCP Tunnel, exposing a small set of read-only, allowlisted tools in an isolated workspace.

Routes code generation tasks between local models and Claude Cloud, optimizing cost by handling simple tasks locally and reserving cloud thinking for complex tasks.

Enables ChatGPT web to interact with local Windows/WSL shell and code workspaces via an MCP server, providing file access, shell execution, and snapshot-based workspace management with per-command authorization.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

Enables Codex to delegate coding tasks to a locally hosted Qwen model through an MCP tool, which can read, write, patch, test, and inspect git diffs inside an allowed workspace.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

Enables Claude Code to hand off bulk, mechanical, read-heavy tasks to a local model, including agentic loops that can read, write, and run commands sandboxed at zero cloud token cost.

Provides 18 tools including calculator operations (add, subtract, multiply, divide, power, sqrt, log, trigonometric functions) and secure sandboxed file operations (read, write, append, delete, list) for LangGraph agents and MCP clients. Features async support, YAML configuration, comprehensive logging, and path traversal protection.

Enables Docker container management and test execution via MCP tools, supporting image building, container operations, and automated test runs.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Bridges Claude with a local Ollama coding model, letting Claude delegate bounded implementation tasks to the local model while retaining reasoning, review, and safety enforcement.

Enables AI clients to interact with and control the Unity Editor through a Python MCP server bridge, allowing natural language-based Unity project manipulation.

A minimal Model Context Protocol server that provides basic utility tools including mathematical operations, text processing, hashing, and JSON validation. Implements JSON-RPC stdio transport for local testing and development.

A starter template for creating MCP servers that work with Puch AI, featuring ready-to-use tools for job searching and image processing. Includes examples for Bearer token authentication, OAuth integration with Google and GitHub, and demonstrates user-scoped data management.