Natural-language MCP tool dispatcher powered entirely by TypeSafe's Jev — no general-purpose LLM. Discovers a simple MCP server's tool signatures at runtime and uses Jev's typed primitives (Choice/Nou
View on GitHub ↗Zero general-purpose LLM calls — anywhere in this pipeline, not for picking the tool, not for reading a parameter's value out of a sentence, not for anything. This is a proof of concept for a different way to do MCP tool dispatch: given a simple MCP (Model Context Protocol) server — one whose tools take primitive-typed parameters — this script dynamically discovers its tool signatures at runtime and uses Jev — TypeSafe's System One reasoning model — to route a plain natural-language command to the correct tool and extract its arguments straight out of the sentence, using only Jev's typed primitives (Choice / Noul) instead of free-text generation. The dispatcher logic never hardcodes a specific tool name, parameter name, or parameter count. It is not a claim that this works against an arbitrary MCP server unconditionally — see Scope and caveats for exactly what the input text and the tool registry need to look like.
Every decision — which tool to call, which words belong to which argument, how many independent actions a command describes, whether a number is spelled out in words — is made by asking Jev one typed question and reading back a probability, never by asking a model to generate text.
Traditional function-calling asks one model to both pick a tool and free-form-generate its arguments as text, then hopes the JSON parses and the types line up. This does the same job with Jev's typed primitives instead, which keeps every step inspectable and cheap:
From the project README.
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