"IBM MCP Context Forge - Model Context Protocol Framework" matching MCP servers:

Provides live web and document intelligence, including search, company news, scraping, crawling, structured extraction, document parsing, brand intelligence, screenshots, website monitoring, and batch jobs.

A lightweight MCP server for semantic search over markdown knowledge bases, enabling AI coding agents to index, search, and answer questions from local markdown documents.

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

An MCP server that integrates AI retrievals with NASA's Common Metadata Repository (CMR), allowing users to search NASA's catalog of Earth science datasets through natural language queries.

Enables local-first context retrieval and management from JSONL and Markdown sources through MCP, with a rebuildable full-text search index and support for stable reference pagination.

Enables agents to query a local macOS archive of Knowledge and browser history through read-only stdio MCP tools for status, timelines, search, original records/blobs, schemas, bounded SQL, and usage or domain summaries.

MCP proxy that reduces context usage through semantic tool routing, enabling on-demand discovery and routing of relevant tools.

Enables MCP clients to look up domains, URLs, IPs/ASNs, email addresses, phone numbers, crypto wallets, and business records; run autonomous investigations; collect crawl artifacts; and perform evidence-backed scam checks with traceable provenance.

Enables ChatGPT to search, read, and organize your Google Keep notes through read-only MCP tools, including full note retrieval, label listing, recent-note browsing, and task extraction. Notes refresh automatically from your connected account without any local database or write access.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

Enables buyer agents to resolve sourced merchant records, search and compare offers while preserving unknowns, obtain merchant-owned safe actions with approval and recovery rules, and run an explicit x402-paid fresh inspection.

An MCP server that enables semantic search over local files or GitHub repositories by indexing content into a serverless vector database, allowing AI assistants to understand meaning rather than just keywords.

Local-first memory server that stores notes, contacts, and future data as a unified entity graph, providing hybrid retrieval (vector + keyword) for AI assistants via MCP.

A server that enables language models to perform web searches through SearXNG using the Model Context Protocol standard.

Provides AI agents with a persistent, searchable knowledge library via MCP tools, allowing them to create books, manage pages, perform semantic search, and retrieve usage guides.

Local MCP server that provides semantic search (RAG) over code repositories, enabling AI clients like Claude and Gemini to access project context without manual re-upload.

An MCP server serving a curated corpus of thinking techniques for AI agents, with tools to classify intents, find and apply techniques, and verify their effectiveness.

A middleware server that intelligently routes AI model queries to appropriate data sources, providing contextual information to enhance AI responses.