"Jest" matching MCP servers:

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

Enables deep web search across multiple providers including Google, Bing, Brave, DuckDuckGo, and Perplexity, with support for comprehensive AI-powered research using intelligent multi-engine queries.

A lightweight MCP server that provides a unified interface to various LLM providers including OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama.

Enables querying and managing personal/team internal knowledge from sources like Slack, Gmail, and Drive through semantic search and retrieval.

Enables semantic search and retrieval of personal and team knowledge from connected sources like Slack, Gmail, Google Drive, and Dropbox, with the ability to save new information for future recall.

MCP server that retrieves up-to-date Google Maps Platform documentation and code samples to ground AI-generated code in official guidance.

A serverless deployment for running Model Context Protocol (MCP) servers on Cloudflare Workers without requiring authentication, allowing users to easily deploy and customize AI tools accessible via SSE endpoints.

Enables MCP-compatible AI clients to extract live web content and convert it into structured Markdown for LLM ingestion, RAG pipelines, and agentic workflows.

Enables AI agents to perform offline cybersecurity research and penetration testing by querying a local knowledge base of curated security data, with tools for searching, answering, and status checking.

Enables building and querying knowledge graphs by ingesting documents into Neo4j using Gemini for entity extraction, and exposes MCP tools for graph health, document ingestion, and knowledge base querying.

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A Model Context Protocol server that bridges Microsoft Teams with MCP-compatible clients (LLMs, agentic frameworks, CLI), enabling chat integration, message search, and event streaming without traditional REST API endpoints.

Enables semantic search and document retrieval from OpenAI Vector Store, allowing users to search documents using natural language queries and fetch complete document contents through ChatGPT.

A local Retrieval-Augmented Generation system that enables users to ingest markdown files into a FAISS-powered vector knowledge base for semantic search. It provides tools for document indexing and context retrieval to support informed LLM queries without external dependencies.