MCP-Ollama Client

The MCP‑Ollama Client is a lightweight, command‑line gateway that bridges local large language models (LLMs) with any number of Model Context Protocol (MCP) servers. By running entirely offline on a single machine, it eliminates the need for cloud APIs or external authentication keys. At launch the client automatically starts every MCP server listed in a single file, pulls each server’s tool schema, and prefixes the tools with their server name (e.g., or ). This merged, collision‑free tool list is then supplied to the local LLM, which decides in real time which server’s capabilities to invoke for each user query.

Developers benefit from an out‑of‑the‑box, multi‑server environment that can host a database interface, a file system explorer, or any custom MCP service side‑by‑side. The client’s design keeps all components local: the LLM runs via Ollama, and each MCP server communicates over standard input/output. This architecture not only preserves privacy but also gives developers fine‑grained control over the tools available to an AI assistant, enabling rapid experimentation and deployment in secure or offline settings.

Key features include:

• Local LLM first: The default model is , but any function‑calling model available in Ollama can be used, removing cloud dependencies.
• Multi‑server out‑of‑the‑box: A single configuration file defines all MCP servers, making it trivial to add or remove services without modifying the client code.
• Collision‑free tool names: Tool identifiers are automatically prefixed with the server name, ensuring that similarly named tools from different servers never clash.

Typical use cases span data‑driven assistants that query PostgreSQL databases, file‑system explorers for document retrieval, or custom tools built on the MCP framework. In a research lab, a scientist can run a local LLM to analyze experimental data while the client transparently calls an MCP server that interfaces with their laboratory instruments. In a DevOps context, the same setup can expose infrastructure APIs and log files to an AI that helps diagnose system issues.

By integrating seamlessly into existing MCP workflows, the MCP‑Ollama Client empowers developers to create powerful, privacy‑preserving AI assistants that combine the flexibility of local LLMs with the modularity of MCP servers—all without leaving their command line.