Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.
Caution. Specific findings reduced this grade. They are listed on the page. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.
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⚡ Connect GitHub → continuous verification on every pushwhy connect →Who stands behind it
jonigl
Source: github_topic
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Install from
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OLLMCP_API_KEY2. The $ environment variable (provider-agnostic, applies to whichever provider you selected with --provider).Tool annotations
No tools have read-only/destructive annotations
Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.
All four hints declared on every tool
1/1 tools missing one or more hints — dynamic_tool_238 (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint). OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.
For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.
Tests exist
No test files found
Add tests that exercise each declared tool.
No access to sensitive paths
Reads sensitive paths: ~/.config/ollmcp
Remove reads of sensitive system paths. If you genuinely need them, document why in the README.
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[](https://m8ven.ai/mcp/jonigl-mcp-client-for-ollama-1ikr7u)?variant=verified from the URL.Vetting this one by hand? Tool Check is an MCP that scores other MCPs. Add it once and ask Claude, ChatGPT, or any MCP client to grade a server, surface CVEs, check the publisher, and suggest safer alternatives — before you install.
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