Cut your AI agent token bill.

Your MCP servers, on a token diet

One command wraps every MCP server you use — GitHub, databases, browsers and more — behind Tokenade's proxy. Verbose JSON results are compacted in transit by tool-aware compactors, tool manifests are stripped down to their callable skeleton, and tools that can't run on your machine aren't even advertised to the agent.

A local search that understands your code

Tokenade indexes and parses your project, then hands your agent real code-intelligence tools: semantic search to find code by meaning, map for the repo structure, query to jump to any symbol, skeleton for a file's signatures, impact for dependents. Because Tokenade knows what's a function and what's a variable, your agent stops reading whole files just to find one.

A context window managed like a budget

Tokenade knows exactly when your prompt cache expires, and compacts old context before it gets re-billed as fresh input. Resuming an old session? Stale oversized results are masked — and recoverable on demand. And when several commands can run at once, Tokenade batches them, turning multi-round back-and-forths into a single turn.

Your agent reads the whole repo, not just the code

Point your agent at a PDF spec, a spreadsheet of results or a recorded meeting and it improvises — its built-in reader if it has one, otherwise whatever converter it can shell out to. You get an answer, and the raw output lands in your context at full price. Tokenade extracts them properly instead: over a hundred formats read and searched like any other file, media as metadata plus a transcript, images converted to something your agent can actually display.

Works on every agent Tokenade supports — nothing to configure.

Tokenade stops secret leaks

By default, Tokenade redacts secrets before they are ever sent to your AI model. What your agent reads on your machine, the model — and its provider — never sees.