Official MCP server for Replicate, enabling agents to run ML model inference across thousands of open-source models.

MCP server for Perplexity's AI-powered search API, providing sourced answers with citations for agent research tasks.

Access OpenAI models including GPT-4o, o1, DALL-E, and Whisper from MCP-compatible agents. Use OpenAI capabilities as a tool inside any MCP workflow.

Ultra-fast LLM inference via Groq. Access Llama 3, Mixtral, and Gemma models at speeds up to 800 tokens/sec from any MCP-compatible agent.

Access 900,000+ models on HuggingFace Hub. Run inference, search models, retrieve datasets, and interact with Spaces from AI agent workflows.

Access Cohere Command and Embed models from AI agents. Generate text, create embeddings, rerank search results, and build RAG pipelines via Cohere API.

Access Mistral AI models including Mistral Large, Codestral, and Pixtral from MCP-compatible agents for text generation, code completion, and vision tasks.

Call Anthropic Claude models as tools within MCP-compatible agent workflows. Access Claude 3.5 Sonnet, Haiku, and Opus for text generation, analysis, and reasoning.

Together AI inference API via MCP. Run open-source LLMs — Llama, Mistral, DBRX, and more — with fast parallel inference at scale.

Local LLM inference via Ollama. Run Llama, Mistral, Gemma, and other models locally — no API keys, no data leaving the machine.

Live library documentation fetcher for LLMs. Resolves library names to current API docs, preventing hallucinations on outdated APIs.

Structured multi-step reasoning for complex problems. Enables agents to break tasks into explicit thought chains, revise reasoning, and build toward solutions methodically.

Official Qdrant MCP server for storing, retrieving, and searching vector embeddings in the Qdrant vector database.

Persistent memory layer for AI agents. Store, search, and retrieve user preferences, conversation history, and learned facts across sessions. Official Mem0 MCP server.

LangSmith LLM observability via MCP. Trace agent runs, inspect prompts and outputs, evaluate quality, and debug complex chain failures.

Weights & Biases ML experiment tracking via MCP. Log runs, compare metrics, manage model artifacts, and query training history from agents.

Official MCP server for Langfuse LLM observability. Access and manage prompts, traces, and datasets through the Model Context Protocol.

MCP server for Comet Opik, providing unified access to LLM prompts, projects, traces, and evaluation metrics from your IDE.

MCP server for Arize Phoenix AI observability. Explore projects, traces, spans, prompts, datasets, and experiments via the Model Context Protocol.

Official MCP server for Confident AI and DeepEval. Run LLM evaluations, manage prompt templates, pull datasets, and trigger cloud evals from your editor.

MCP server for Braintrust AI evaluation and observability. Access experiments, datasets, scoring functions, and production logs for LLM quality management.

Local MCP server that packages LLM evaluation gates as reusable CI/CD primitives. Run datasets against models, score with LLM-as-judge, enforce quality thresholds.

Benchmarking framework by Accenture for evaluating LLM tool-use via MCP. End-to-end pipeline assessing how effectively models discover, select, and use tools.

MCP server exposing Promptfoo eval and red-team testing tools to AI agents. Run prompt evaluations, security tests, and quality checks from your IDE.

Access Google Gemini models via MCP. Run text generation, multimodal inputs, code execution, and grounding with Google Search through the Gemini API.

Integrate xAI's Grok models into agent workflows. Access Grok's real-time knowledge, large context window, and reasoning capabilities via the xAI API.

Route LLM requests across 200+ models via a single MCP interface. Access GPT, Claude, Gemini, Llama, Mistral, and more with unified pricing, fallbacks, and load balancing.

Access Amazon Bedrock foundation models via MCP. Invoke Claude, Titan, Llama, Mistral, and other models hosted on AWS Bedrock directly from agent workflows.

Universal LLM gateway via MCP. Route agent requests to 100+ LLM providers — OpenAI, Anthropic, Bedrock, Gemini, Groq — through a single interface with cost tracking and load balancing.

Access Azure-hosted OpenAI models via MCP. Use GPT-4o, o1, and other models deployed in your Azure OpenAI resource with enterprise compliance and private networking.

Access DeepSeek reasoning and chat models via MCP. Run DeepSeek-R1 and DeepSeek-V3 for cost-efficient reasoning tasks, long-context analysis, and code generation.

MCP server for LlamaIndex — the leading data framework for LLM applications. Query knowledge bases, run RAG pipelines, manage document indexes, and connect agents to structured data.

MCP server for Haystack by deepset — the open-source NLP framework for building production-grade RAG and search pipelines. Run pipelines, query document stores, and manage AI components.

MCP server for the Cerebras Inference API — the world's fastest AI inference engine. Run Llama and other open models at 1,800+ tokens/second for latency-sensitive agentic workloads.

MCP server for MLflow — the open-source ML lifecycle platform by Databricks. Log experiments, compare runs, register models, manage the model registry, and track artifacts from AI and ML pipeline agents.

MCP server from Guidepoint giving AI research workflows access to 100,000+ expert interview transcripts, industry insights, and primary research intelligence directly inside Claude and other MCP-compatible tools.

MCP integration for Google AI Edge Gallery enabling on-device AI models running locally on Android to connect with external tools and data sources. Supports the Model Context Protocol for extending local LLM capabilities with tool use, persistent chat history, and notification reminders without cloud dependency.

Industrial-grade speech recognition toolkit from ModelScope with MCP integration. Delivers 170x realtime transcription speed across 50+ languages with speaker diarization, emotion detection, and streaming support. Provides an OpenAI-compatible API and exposes ASR capabilities as MCP tools for AI agent workflows.

Self-learning vector memory MCP server that improves search quality up to 36% through agent feedback loops. Consolidates vectors, indexes, learning state, and a cryptographic audit trail into a single portable .rvf file. Provides tiered memory with automatic quality refinement for AI agent workflows.

Tiered memory system MCP server for AI agents that stores and recalls episodes, facts, preferences, and reflections. Provides local-first portable memory that works across devices. Organizes agent knowledge into structured tiers for efficient retrieval and long-term context preservation.