7 Tools to Cut Your Coding Agent's Token Bill (2026)

RTK (Rust Token Killer) is a single Rust binary that hooks into your agent and rewrites common commands (ls, cat, grep, git, test runners, linters, docker) into compact versions. Test runs collapse to failures only, git log keeps hash, author and subject, and directory listings become trees with counts. The project claims 60 to 90% smaller output on common dev commands. It is also upfront that this only covers bash output, which is one part of your bill. Telemetry is off unless you opt in.

Install with brew install rtk, then rtk init -g. One gotcha: another crate named rtk exists, so check that rtk gain works after install. That same command shows the savings from your own use.

Headroom is an open source compression layer between your agent and the model. It squeezes JSON, logs, code and chat history on your machine, keeps the lines that matter and caches the originals so the agent can pull them back. Its README reports about 20% fewer tokens for coding agents and 60 to 95% fewer on JSON-heavy tool output, with the same answers on its benchmarks. The MCP server exposes headroom_compress, headroom_retrieve and headroom_stats.

Install with uv tool install --python 3.13 "headroom-ai[all]", then headroom wrap claude (undo with headroom unwrap claude). Two things to know: an anonymous usage beacon is on by default (set HEADROOM_TELEMETRY=off or DO_NOT_TRACK=1 to turn it off), and headroom wrap also installs Serena unless you pass --code-memory none.

Context Mode sits between your agents and the model. Its free Engine is a local plugin that works through MCP and hooks in 18 AI coding tools. It sandboxes tool output so only the answer reaches the model, keeps session memory, loads skills only when a task needs them and makes every prompt and command searchable.

It does more than compression, with rules for what agents may read, run and reach, and a paid hosted control plane for team features. If you want one plugin for output folding and memory, start with the Engine from the GitHub repo.

XERJ is a local Rust search engine that indexes a folder (code, docs, logs, PDFs) so the agent queries ranked passages with file:line results instead of reading files one by one. It supports BM25, vector and hybrid search, go-to-definition lookups and an agent memory namespace. The project reports a 2.7x cut in output tokens at the same solve rate in its own case study, based on agents indexing reference repos before writing code.

Install with curl -fsSL https://xerj.org/get | sh, run xerj init to wire it into Claude Code or Cursor, then xerj autoindex ~/my-project. The --insecure dev mode disables TLS and auth, so keep it to a single user on localhost.

Serena gives coding agents IDE-style tools over MCP: symbol-level retrieval, find-references, cross-file renames and edits. Looking up a symbol instead of grepping lines and reading whole files means less code ends up in context.

Install with uv tool install -p 3.13 serena-agent, then launch serena start-mcp-server. Skip the older marketplace one-click installs and use that command. If you already use Headroom's default wrap, you have Serena installed.

Context7, built by Upstash, serves version-specific docs and code examples to Claude Code, Cursor, Codex and other agents through a hosted MCP server or the ctx7 CLI. When an agent writes against an old API, you pay for the failed attempt, the error output and the retry. Pulling the right docs up front avoids that loop.

Set it up with npx ctx7 setup. The free tier covers 1,000 API calls a month for public repos. Pro is $10 per seat per month and adds private repo parsing.

mcpc is Apify's open source command-line MCP client. It maps every MCP operation to a shell command, so Claude Code or Codex can use any MCP server through bash instead of loading dozens of tool definitions into context. Progressive tool discovery means the agent only reads the schemas it needs.

Install with brew install mcpc (or npm install -g @apify/mcpc), then mcpc connect <server> @name and mcpc @name tools-list. It keeps persistent sessions to several servers, stores OAuth credentials in the OS keychain and never calls an LLM on its own.