"Project Management for Aircraft Development" matching MCP servers:

Local workspace memory for Claude Desktop. Indexes documents into a vector store with hybrid search, cross-session memory, auto-learn, and knowledge graph.

Enables coding agents to retrieve compact, cited repository maps through MCP tools such as search, symbol inspection, flow investigation, and deep context loading.

Enables users to interact with an e-commerce shopping assistant using natural language to search products, check prices and ratings, compare items, and get personalized recommendations.

A Python MCP server that gives LLMs persistent, searchable access to project context — documentation, architecture decisions, and session notes.

Hardware-accelerated codebase mapping that indexes Git repositories into Postgres/pgvector and serves code search, relationships, and static analysis results via a stdio MCP server.

It enables users to interact with a codebase through hybrid retrieval, code graph navigation, impact analysis, and context preparation for AI coding agents.

A self-contained Claude Code plugin that profiles a project by running a fixed DAG to emit agent-facing context pages, a human/developer guide, and a queryable vectorstore.

Enables hybrid retrieval-augmented generation with semantic and keyword search over documents, supporting multiple formats and providing MCP integration for Claude Desktop.

Enables agents to search and retrieve past workspace conversations, dialogue transcripts, and markdown artifacts through local BM25 retrieval, providing cross-conversation architectural recall with low-latency, offline operation.

Routes coding agents to the most relevant project documentation (decisions, intent, constraints) with provenance and freshness, providing tools for task routing, knowledge search, and document context.

Provides project-aware context for coding agents by selecting relevant AGENTS.md, docs, module paths, and decision records based on task, reducing redundant context loading via MCP stdio.

Enables semantic search over a software project's Markdown and text documentation by indexing document chunks in Qdrant and exposing retrieval through MCP tools.

Stores manual project memories, enables semantic retrieval, and tracks per-memory confidence using PostgreSQL with pgvector and OpenAI-compatible embeddings.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A proof of concept MCP server for Apache OFBiz

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Jira Service Management (beta): https://www.cdata.com/download/download.aspx?sku=GKZK-V&type=beta

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Enables Claude Code to search your local project notes and list indexed projects through hybrid keyword and semantic retrieval, returning relevant snippets with file and line references.

Enables Claude to perform hybrid search across local documents by combining semantic vector retrieval and BM25 keyword matching for optimal context recovery. It supports multiple file formats including PDF, CSV, and Markdown, leveraging local Ollama models for private and efficient document querying.

Personal local AI memory/document MCP that manages short and long-term memories and Markdown documents, with tools for import, search, and retrieval.

Allows programmatic management of a Dify instance, including listing and creating datasets, managing applications, and tool providers.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

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

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

A demonstration server implementing the Model Context Protocol (MCP) with both STDIO and Server-Sent Events (SSE) support, featuring a word reversal tool that transforms input text by reversing characters.

A lightweight, dependency-free MCP server that answers cited queries over a Tero corpus index.json via stdio JSON-RPC 2.0, with honest refusal semantics and no silent empty results.

Facilitates access and management of Langfuse prompts through the Model Context Protocol, enabling prompt discovery, retrieval, and integration within clients like Claude Desktop and Cursor.

Enables natural language management of Hammerspace storage clusters with automated file ingestion, tagging, tier management, and vector embedding generation. Supports real-time file monitoring, multi-format document processing, and Kubernetes-based ingestion workflows with Milvus integration.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.

Turns any static website into an MCP-searchable knowledge base by deploying a Cloudflare Worker that provides full-text search tools, enabling AI assistants to search and retrieve content from your site.

An integration server implementing the Model Context Protocol that enables LLM applications to interact with Milvus vector database functionality, allowing vector search, collection management, and data operations through natural language.

Enables natural language interaction with heterogeneous databases (MySQL and PostgreSQL) for CRUD operations across customer, product, and sales data with intelligent query routing and visualization capabilities.

MCP server for searching, reading, listing, writing, and appending Markdown wiki content using RAG with ChromaDB.

Provides persistent, searchable memory for MCP-compatible AI coding tools, allowing notes added from one tool to be retrieved from another.

Enables AI clients to search and analyze code/docs through a central Pinecone-backed vector store, inspect project inventories and git sync status, rank work by urgency, and perform deep architectural audits via MCP.

Deploys and manages MCP tools on Amazon Bedrock AgentCore Runtime, enabling knowledge base retrieval and AWS infrastructure management through Streamlit applications.

Search reusable technical experience from AI agents, inspect evidence and limitations, and discover public agent Trust Passports through seven anonymous read-only MCP tools. Apache-2.0 integrations, examples and documentation connect to the separately governed hosted Remnant service. Agent OAuth and Candy are separate surfaces.

It converts documents to Markdown or docling JSON for AI agents. That covers PDFs with layout analysis, table structure and OCR, plus DOCX, PPTX, XLSX, HTML, EPUB, e-mail, images and audio. It serves MarkItDown's "convert_to_markdown" tool under the same name and contract, along with "convert" and "list_input_formats".

Self-hosted long-term memory gateway for AI clients, deployed to your own Cloudflare account (Workers + D1 + Vectorize). It captures conversations, consolidates them overnight, and exposes MCP tools to search, recall and write memories from any MCP client.