"Co-op" matching MCP servers:

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables OMP and Pi hosts without the extension to use OpenViking-backed durable conversation capture, scoped recall, verified archives, explicit memory tools, and cross-agent workspace handoffs through eleven viking_* tools and /ov.

An MCP server for querying Colombian legislative norms and their current legal effect, with read-only tools for normativity search and validity consultation. It provides provenance-backed data with explicit citations to official sources.

A personal memory MCP server for Obsidian/markdown vaults that provides hybrid retrieval (semantic, keyword, tag, time-aware co-occurrence) and is shared across multiple AI clients.

Enables AI clients to explore MCP concepts, retrieve quickstart guides, and ask questions with Redis-cached answers, supporting deployment on Cloudflare Workers and Docker.

Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Exposes AgentHive's member-level calls—including retrieve_context, log_session, create_agent, list_agents, create_task, and list_tasks—as native tools for Cursor and Claude Code. It lets IDEs spawn a stateless local subprocess that makes plain HTTP calls to an existing AgentHive instance, so agents can retrieve reviewed team memory and log sessions without hand-written HTTP instruction blocks.

Trust and quality infrastructure for AI agents. 233+ quality-scored capabilities for company data, compliance checks, financial validation, and more. Every capability has a transparent SQS quality score. Audit trails on every call. EU AI Act support.

Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.

Provides AI agents with structured knowledge about 67+ generative AI models, including model recommendations, prompt formatting, parameter guidance, and validation. It acts as a prompt engineering co-pilot that helps agents use their existing tools more effectively.

Exposes a Neo4j knowledge-graph index over personal markdown notes to LLM agents via MCP, enabling semantic search, tag navigation, and relationship discovery.

Provides tools for searching Agent8 game development code examples and system prompts to assist in Agent8 SDK development.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

Search 1,500+ pre-verified, cited knowledge units across 16 domains. 6 tools: query, batch query, get unit, list domains, suggest topics, report issues. Free, no API key required.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Enables natural-language semantic search of a project's code through a local vector index, so questions that plain grep cannot match return ranked file:line references. It also indexes or refreshes projects on demand, reports index status, and optionally flags near-identical code across files.

Enables coding agents to query a team knowledge base via MCP, performing semantic search and asking questions that return grounded, citation-backed answers from ingested documents.