"How to test a React app" matching MCP servers:

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

AI reads your codebase like a book - one page at a time. Pharaoh gives it the index and a map of how every chapter connects.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

Enables MCP-compatible coding harnesses to read Amp threads as Markdown, with pagination and filtering options, through a read-only interface.

Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

A personal digital twin MCP server that manages professional context, including skills, experience, and project learnings. It allows AI assistants to retrieve and update user preferences and career interests across different development environments.

Provides a compiled knowledge substrate, extracting atomic claims from an append-only capture log and querying a bitemporal claim graph over MCP. Read-only by default, with opt-in writes for trusted sources.

An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

A productivity coaching assistant designed for ADHD support that provides intelligent task management, goal tracking, and personalized recommendations. It utilizes a persistent memory system to learn user patterns and preferences, helping to reduce decision paralysis through actionable suggestions.

Integrates with Get笔记 (GetBiji) API to enable AI-powered knowledge base search and retrieval. Provides tools for enhanced semantic search, raw content recall, and rate limit monitoring.

A local-first MCP server that turns browser bookmark exports into a searchable knowledge base with classification, merging, full-text indexing, and Chrome integration.

Enables AI agents to persist, search, and evolve knowledge through a Markdown vault with a typed knowledge graph and MCP interface.

Local-first MCP server that binds to a project opened by the Seojeom desktop app and serves its local wiki and graph data over stdio, enabling project-aware reading, searching, and writing of wiki and graph content.

Enables AI assistants to search, create, and manage knowledge graphs in Aiqbee brains for architecture, portfolio, and digital strategy.

Enables MCP agents to query a local, cross-app personal model built from macOS activity, providing search, receipts, and model tools.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.