"Tor Project" matching MCP servers:

Enables MCP-compatible agents to route HTTP requests through the Tor network, providing anonymity and access to .onion services. Includes tools for fetching URLs, checking exit IP, and forcing new Tor circuits.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

Enables coding agents to persist notes, decisions, requirements, and learnings per project in SQLite and retrieve them across sessions via search and status tools.

MCP server for Project CPU, a blockchain game on EVM. It lets an AI agent play on your behalf: read the world map, reveal cells, build and mine, craft, move resources, trade at marketplaces, and cash out to on-chain $CPU.

Provides AI-driven project memory management through structured prompts that help Claude parse tasks from specs, review code changes, sync with commit history, and maintain project documentation without directly accessing files.

A cross-project knowledge graph for MCP that maps features across mobile, backend, and admin codebases, giving AI agents full-stack context.

Enables project task management through MCP tools to create, list, and update tasks, with SQLite persistence.

Semantic search over project-specific decision rules using Chroma, enabling LLMs to retrieve relevant context.

Enables searching and retrieving icons from The Noun Project API with advanced filters for style, color, and size customization.

A persistent memory layer for Claude Code that maintains project information, technology stack, tasks, decisions, and session history between coding sessions, eliminating the need to re-explain project context.

A Model Context Protocol (MCP) server that enables AI applications to access and analyze local code repositories without manual uploads, providing file listing, content reading, code searching, and project structure analysis capabilities.

Enables coding agents to incrementally index project text and code, persist decisions and constraints with clear sources, and assemble focused project context across sessions via MCP.

An open-source MCP server that automates project customization by analyzing your codebase and generating AI-ready configuration files based on industry best practices.

An MCP server that provides access to project files and their contents, allowing users to retrieve file data from specified project directories with error handling and configuration options.

Enables AI agents and project managers to turn GitHub Projects v2 into an autonomous project-management layer, handling task checkout, atomic claims, heartbeats, reviews, token budgets, and AI-powered PRD, sprint, triage, and roadmap workflows. It also provides GitHub Actions, Releases, Branches, MCP Resources, and MCP Prompts support with GitHub-native storage.

Enables coding agents in different editors and MCP clients to share messages, project context, notes, task ownership, handoffs, and advisory file claims through a local SQLite-backed coordination server. Supports MCP stdio, MCP Streamable HTTP, a JSON HTTP API, and a local CLI for multi-project agent collaboration.

Implements a Model Context Protocol server for intelligent end-to-end requirement management and development automation, integrating with Feishu project systems.

Enables AI agents to query a repository's verified semantic model, including capabilities, ownership, contracts, constraints, impact, health, and verification status, without re-deriving project facts. It exposes read-only tools for inspecting, reasoning about, and verifying the provenance-tracked surface.

Enables AI agents and human managers to orchestrate GitHub-based project work by self-assigning tasks, coordinating swarms, tracking token budgets, generating PRDs, planning sprints, triaging issues, and materializing tasks as GitHub issues, milestones, and project views.

Enables multi-project workspaces to share structured notes, API contracts, and handoff messages via a local SQLite database, with versioning and read tracking.