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    LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.
    21 npm
    1
    MIT
  • A
    license
    A
    quality
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    Enables document Q&A with grounded citations using the official Gemini File Search API. Upload documents, create stores, and ask questions that return exact passage citations.
    7
    10 npm
    2
    MIT
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    Get access to real-time SEO data, including: keyword insights, backlink data, traffic estimates and more. Allow AI tools and Large Language Models (LLMs) to tap into the real-time SEO Review Tools API with natural language commands.
    8
    8 npm
    7
    MIT
  • A
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    C
    maintenance
    MCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.
    MIT
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    A multi-function Streamable HTTP MCP tool aggregation server that provides web search via Brave, Exa, and SearXNG with multi-key rotation and cross-provider fallback, and supports extensible tool families (URL fetch, code search, RAG) through a pluggable architecture.
    MIT
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    maintenance
    Enables clinical question answering via OpenEvidence with citation verification, including tools to ask questions, retrieve results, and follow up, plus an integrated skill to check citations against primary sources.
    8
    MIT
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    Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.
    1
    9 npm
    1
    MIT
  • A
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    A collection of tools that enhance MCP-based workflows with caching, retry logic, batch operations, and rate limiting capabilities.
    7
    10 npm
    MIT
  • A
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    quality
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    An MCP server providing 22 pay-per-call utility tools for AI agents (scrape, validate, embed, store, moderate, notify, convert, prevent loops) without accounts or API keys, using USDC payments via the x402 protocol.
    17
    77 npm
    1
    MIT
  • A
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    Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity. * Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2
    54
    52
    MIT
  • F
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    C
    quality
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    An MCP server that connects AI assistants to a Neo4j graph database, enabling querying of movie data through tools like graph statistics, genre-based search, and movie details, along with advanced features such as LLM sampling and completions.
    4
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    A Model Context Protocol server that exposes over 200+ APIs from API.market as MCP resources, allowing large language models to discover and interact with various APIs through natural language commands.
    34
    31 npm
    4
    MIT
  • A
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    Provides access to OpenAI's advanced models (including o3) with integrated web search, Python code interpreter, and combined analysis capabilities. Enables users to perform web searches, execute code in sandboxed environments, and combine search with analysis through natural language.
    MIT
  • A
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    quality
    C
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    An MCP server that gives AI coding assistants access to up-to-date API documentation via RAG by crawling documentation sites, indexing them into a vector store, and enabling semantic queries.
    MIT
  • F
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    Enables interaction with the Sond Core API through the Model Context Protocol. Auto-generated from the OpenAPI specification at https://core-api-lb.sond.com/api-json to provide programmatic access to Sond's services.
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  • F
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    Enables interaction with Spinitron's radio playlist management and broadcasting data through a Multi-Agent Conversation Protocol interface, allowing users to query and manage radio station playlists, spins, and other broadcasting data via natural language.
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  • F
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    Enables MCP-compatible clients to retrieve relevant document chunks and fact-check generated answers against context, classifying them as fully supported, partially supported, or unsupported.
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