Agentic-research MCP Server

Agentic-research is an MCP integration. Local research agent that verifies its own answers. Runs on Gemma 3 4B + Ollama, $0/query.

Packages and local setup

The published pypi package is agentic-research-engine, version 0.1.3. Its declared MCP transport is stdio.

The package declares OPENAI_BASE_URL: Any OpenAI-compatible endpoint. Default: OpenAI cloud. Use http://localhost:11434/v1 for Ollama.; OPENAI_API_KEY: API key for the endpoint above. Use 'ollama' as a sentinel value when running locally against Ollama.; MODEL_SYNTHESIZER: Model identifier used for the synthesize node. Defaults to 'gpt-5-mini'; set to 'gemma3:4b' for Mac-local Ollama.; MODEL_PLANNER: Model for the plan / classify / critic / compress / verify nodes. Defaults to 'gpt-5-nano'.; EMBED_MODEL: Embedding model identifier (for retrieval + memory). Default 'text-embedding-3-small'; use 'nomic-embed-text' on Ollama.; SEARXNG_URL: Base URL of the SearXNG meta-search instance. Default http://localhost:8888.; LOCAL_CORPUS_PATH: Path to an index directory built via scripts/index_corpus.py. When set, local corpus hits augment web search.; ENABLE_RERANK: Set to '1' to enable the BAAI/bge-reranker-v2-m3 cross-encoder rerank stage. First run downloads ~560MB.; ENABLE_FETCH: Set to '0' to skip the trafilatura full-page fetch stage. Default '1'..

Before connecting

Check the maintainer’s instructions for account access, authentication and the supported client configuration. Once connected, inspect the tools your client receives and try a small task that matches the server’s stated purpose. The registry description does not include a verified, complete tool list.

Project and source

View the publisher’s registry entry · Project repository. This profile uses version 0.1.3 from the registry. Registration identifies the publisher namespace; it does not establish that this is a first-party integration for every service it connects.

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