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rayhankhilji/jellybean

A token-frugal MCP server that gives coding agents structural understanding of a codebase: repo maps, symbol outlines, ranked search, import tracing, and parsed diagnostics — every result under a toke

⭐ 3 stars
⑂ 1 forks
TypeScript
momentum ▲ 8.0
created 2026-07-25
on radar since 2026-07-29
ai-agentsclaudecode-intelligencedeveloper-toolsllm-toolsmcpmodel-context-protocoltypescript
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About jellybean

An MCP server that lets coding agents understand a codebase without reading it.

Repository maps, symbol outlines, ranked search, import tracing, change review, and parsed diagnostics — every result under a token budget it actually honours.

Most MCP servers are thin wrappers around readFile and grep. That makes them easy to write and expensive to use. An agent asked to add a field to a service typically burns through something like:

Roughly 14,000 tokens to learn four facts. The context window fills with material the model will never refer to again, and the useful signal is buried inside it.

Jelly Bean attacks this directly. Same task, same repository:

Under 900 tokens, and the agent knows strictly more than it did above — because it also knows what else is in those files, and what depends on them.

Everything here follows from three decisions.

1. Handles instead of dumps. Every result is compact rows carrying an identifier like jb7c1e9a04 that addresses an exact region of an exact file. The agent spends tokens on a body only for the handles it chooses to follow. Handles are content-derived, so the same region always yields the same handle — an agent can tell that a search hit and an outline entry are the same function without expanding either.

2. Budgets are a contract, not a hint. Every tool takes tokenBudget and fits inside it, degrading detail rather than truncating mid-row. The footer always reports what was omitted and names the one call that would reveal it, so a truncated result is a signpost instead of a dead end.

From the project README.

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