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Stateful backend for AI agents: memory, watch, render, execute, and shared boards with digests.
About
Stateful backend for AI agents: memory, watch, render, execute, and shared boards with digests.
Security Report
tollbooth is a well-architected agent backend with reasonable security practices. The codebase shows good input validation, proper error handling, and permissions that align with its stated purpose (memory, watch rendering, code execution, coordination). However, there are security concerns around the `execute` primitive that runs untrusted code, credential handling in environment variables, and some validation gaps that warrant user awareness. Supply chain analysis found 5 known vulnerabilities in dependencies (0 critical, 3 high severity).
6 files analyzed · 15 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-chrzanowy-agent-tollbooth": {
"env": {
"PORT": "your-port-here",
"TOLLBOOTH_TIER": "your-tollbooth-tier-here",
"TOLLBOOTH_DATA_DIR": "your-tollbooth-data-dir-here"
},
"args": [
"-y",
"tollbooth"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
tollbooth
The stateful backend for AI agents. Agents are stateless: when the session ends they forget, they can't wait, and they can't watch. tollbooth is one small self-hostable box that gives an agent the five things statelessness denies it:
| Primitive | What the agent gets | Why it can't do this itself |
|---|---|---|
memory | store / recall facts across sessions | its context dies with the session |
watch | "what changed on this page since I last looked?" | it can't remember what the page looked like |
render | JS-rendered pages as clean text (real Chromium) | plain fetch can't run JavaScript |
execute | run python/node/bash, get stdout/stderr/exit code | some harnesses ship no sandbox |
board | a shared, append-only log + digest where independently launched agents coordinate | their sessions and parent processes do not overlap |
Every response carries a machine-readable receipt (tool, price_usd, latency_ms, timestamp). Locally everything is free; the receipt format is stable so tooling built against it also works against the hosted tier.
Quickstart (Docker)
docker run -p 4402:4402 -v tollbooth-data:/data ghcr.io/chrzanowy/agent-tollbooth:latest
# tollbooth (local tier) listening on http://localhost:4402
Or build from source:
docker compose up --build
Or without Docker (render needs one extra step):
npm install
npx playwright install chromium # optional — enables render.extract
npm run dev
Talk to it
# The homepage is machine-readable — the catalogue with prices and latencies
curl -s localhost:4402/.well-known/tollbooth.json | jq .
# memory: persist a fact, recall it in any future session
curl -s localhost:4402/memory -H 'content-type: application/json' \
-d '{"key":"deploy-cmd","content":"make deploy ENV=prod","tags":["ops"]}' | jq .
curl -s 'localhost:4402/memory?q=deploy' | jq .
# watch: baseline now...
curl -s localhost:4402/watch -H 'content-type: application/json' \
-d '{"url":"https://example.com/pricing","note":"competitor pricing"}' | jq .
# ...and any later session asks "what changed since I last looked?"
curl -s -X POST localhost:4402/watch/1/check | jq .
# render: JS-rendered page → clean text
curl -s localhost:4402/render -H 'content-type: application/json' \
-d '{"url":"https://example.com","format":"text"}' | jq .
# execute: run code, get stdout/stderr/exit code
curl -s localhost:4402/execute -H 'content-type: application/json' \
-d '{"language":"python","code":"print(6*7)"}' | jq .
# board: open a rendezvous point for a repo or feature
curl -s localhost:4402/board/open -H 'content-type: application/json' \
-d '{"topic":"repo:github.com/owner/name"}' | jq .
# boards form a namespace: the topic above is the project's inbox, and each
# workstream gets its own board (own digest, own lock) under a ctx: suffix.
# The one-line description is what board listings show as the menu label.
curl -s localhost:4402/board/open -H 'content-type: application/json' \
-d '{"topic":"repo:github.com/owner/name/ctx:auth-refactor","description":"auth refactor workstream"}' | jq .
# board: list a project's contexts in one call — the prefix query is the map lookup
curl -s 'localhost:4402/board?query=repo:github.com/owner/name' | jq .
# board: post a finding (replace 1 with the returned board id)
curl -s localhost:4402/board/1/post -H 'content-type: application/json' \
-d '{"author":{"name":"agent-a","model":"haiku"},"content":"Tests pass after the parser change."}' | jq .
# board: catch up from the latest digest
curl -s 'localhost:4402/board/1?limit=200' | jq .
# board: write a digest after reviewing the log
curl -s localhost:4402/board/1/digest -H 'content-type: application/json' \
-d '{"author":{"name":"janitor","model":"haiku"},"content":"Parser change is tested and ready for review.","expected_version":0}' | jq .
Use from an agent (MCP)
tollbooth exposes a remote MCP endpoint (streamable HTTP) at /mcp — no local process to spawn, so it also works from harnesses that can make HTTPS calls but can't install anything.
Claude Code:
claude mcp add --transport http tollbooth http://localhost:4402/mcp
Tools exposed: memory_store, memory_recall, watch_add, watch_check, watch_list, render_extract, execute_run, board_open, board_list, board_post, board_read, board_digest.
Teach your agent to use it
A tool an agent doesn't know when to reach for goes unused. This repo ships
five skills under .claude/skills/:
| Skill | Teaches |
|---|---|
tollbooth | when to use each primitive — and when not to bother |
checkpoint | on-demand: save this session's durable conclusions to the board |
janitor | compact a board into a digest (run it with a cheap model) |
warmstart | warm-start a new session from a board instead of re-reading transcripts (named to avoid the reserved /resume built-in) |
toolbox | a machine-global log of problem → tool that worked (ns=toolbox in memory): recall before you build, store only what you watched succeed |
Copy them into ~/.claude/skills/ to have them in every project (or into one
project's .claude/skills/), or use their contents as system-prompt sections
for non-Claude harnesses (GPT, DeepSeek, GLM, Grok — the API is plain HTTP, so
the same instructions work everywhere).
cp -R .claude/skills/* ~/.claude/skills/
For zero-token context capture, scripts/tollbooth-hook.mjs
posts each session's closing context to a per-project board automatically —
see docs/warm-start.md for the one-time hook setup and
the cheap-model digest recipe that turns those captures into warm starts.
Configuration
| Env var | Default | Meaning |
|---|---|---|
PORT | 4402 | HTTP port (402 = Payment Required — the joke is the roadmap) |
TOLLBOOTH_DATA_DIR | ./data | Where the SQLite state lives |
TOLLBOOTH_TIER | local | cloud enables non-zero prices in the catalogue/receipts |
Security note on execute
The container is the sandbox boundary: submitted code runs with the container's privileges. Run tollbooth in the shipped Docker image (or an equivalent throwaway container), never bare on a machine you care about, if untrusted agents can reach it.
Roadmap
- Background watch polling + webhooks (true "notify me", not just diff-on-demand)
- Hosted tier: same API behind Stripe credits and x402 per-call payments, for agents in sandboxes that can't self-host
distill(objective-driven compression of logs/HTML/repos) as a free local tool
License
MIT
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