omnimcp

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Semantic router for MCP ecosystems

*Discover and execute tools across multiple MCP servers without context bloat*

[](https://pypi.org/project/omnimcp) [](https://github.com/milkymap/omnimcp/blob/main/LICENSE) [](https://github.com/milkymap/omnimcp/actions)

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MCP tool definitions consume tokens fast. A typical setup:

| Server | Tools | Tokens | |--------|-------|--------| | GitHub | 35 | ~26K | | Slack | 11 | ~21K | | Filesystem | 8 | ~5K | | Database | 12 | ~8K |

That's 60K+ tokens before the conversation starts. Add more servers and you're competing with your actual context.

Context bloat kills performance. When tool definitions consume 50-100K tokens, you're left with limited space for actual conversation, documents, and reasoning. The model spends attention on tool schemas instead of your task.

More tools = more hallucinations. With 50+ similar tools (like notification-send-user vs notification-send-channel), models pick wrong tools and hallucinate parameters. Tool selection accuracy drops as the toolset grows.

Dynamic tool loading breaks caching. Loading tools on-demand during inference seems smart, but it invalidates prompt caches. Every new tool added mid-conversation means reprocessing the entire context. Your "optimization" becomes a performance tax.

Tool results bloat context too. A single file read can return 50K tokens. An image is 1K+ tokens base64-encoded. These pile up in conversation history, pushing out earlier context.

OmniMCP exposes a single `semantic_router` tool as the only entry point to your entire MCP ecosystem. The LLM never sees individual tool definitions—just one unifie