batchwatch MCP server
Let an AI agent ask batchwatch "should I batch this job?" instead of guessing.
When a developer asks Claude, Cursor, Cline or any MCP-speaking agent "should I
send this to the batch queue or run it synchronously?", this server lets the
agent call batchwatch and get the real queue evidence — the measured wait
distribution, the current conditions, a graded confidence, and how fresh the
data is.
It wraps batchwatch's existing read routes as MCP tools. It is a thin,
faithful proxy: it makes no decision and invents no numbers. Every answer
is the provider's own JSON, passed through verbatim, carrying the n,
confidence, why, basis and freshness the API already returns. If the API
is down or slow, the tool returns an error — never a fabricated figure.
Access & tiers — the same gate as the rest of batchwatch
Because it is a faithful proxy, the server runs on the same tiers as the
batchwatch API — there is no separate MCP plan and no MCP fast lane. Each
tool carries your BATCHWATCH_TOKEN and earns exactly the tier that key earns
anywhere else:
- No token → you read the public data, delayed 15 minutes. You still get
every answer — the distribution, the conditions, the verdict — as fresh as
the open API serves them.
- A token → the agent earns that key's tier and its freshness, volume and
live behaviour. Live figures are what let an agent route real traffic on
the answer, and they are bought here the same way they are bought at the API.
One access model, gated in one place — the batchwatch tier system (see the
Tiers, delay, quota and the free trial reference in the batchwatch API docs).
Tools
Each tool maps to a real route in src/index.js (there is deliberately no
tradeoff tool — /v1/tradeoff is named in the KRAVSPEC but not built yet, and
a tool for a route that does not answer would be exactly the fabricated
capability this project refuses to ship).
should_i_batch | GET /v1/should-i-batch | Given a model and your own max_wait, does the batch queue currently honour it? The verdict. |
estimate_batchtime | GET /v1/estimate-batchtime | How long is my job likely to wait? A distribution, never a single ETA. |
conditions | GET /v1/conditions | Current conditions vs the recent norm — "is it me or them?" |
distribution | GET /v1/distribution | The full measured wait distribution (the raw evidence). |
coverage | GET /v1/coverage | Which provider+model combos have data, and how answerable each is. |
wait | GET /v1/wait | The public "is the queue moving now?" reading (delayed without a key). |
batchwatch reports distributions and current conditions, not point ETAs. A
personal history of 3-minute medians once produced a 480-minute job; "your job
finishes at 14:32" is a lie the one time it matters. The tools' descriptions say
so, so the calling model uses the answer correctly.
Install & run
cd mcp
npm install
node index.js
Requires Node ≥ 18 (uses the built-in fetch).
Configuration (environment)
BATCHWATCH_URL | https://batchwatch.dev | API base. |
BATCHWATCH_TOKEN | (unset) | Optional API key. Without it the data is delayed, not absent — you still get answers, just older ones. |
BATCHWATCH_TIMEOUT_MS | 8000 | Per-call timeout. On timeout the tool errors; it never guesses. |
Wiring into a client
Claude Desktop / Cursor / Cline mcpServers entry:
{
"mcpServers": {
"batchwatch": {
"command": "node",
"args": ["/absolute/path/to/batchwatch/mcp/index.js"],
"env": { "BATCHWATCH_TOKEN": "tk_your_key_optional" }
}
}
}
Tests
npm test
BATCHWATCH_LIVE=1 npm test
The unit tests assert the load-bearing properties: omitted numeric fields are
never sent as 0; the provider JSON is passed through unchanged; only the real
routes are exposed (no tradeoff); and an API error yields an error, never a
number.
Publishing (registry reach — the point of #57)
The highest-leverage distribution channel for a 2026 dev tool is being the
answer an agent reaches for by default. Once this is published so agents can
install it, batchwatch wins the call instead of merely being mentioned. Targets:
the Anthropic MCP registry, Smithery, and
mcp.so. The package is publish-ready (bin: batchwatch-mcp,
zero build step); registry submission is tracked on Vikunja task #57.
Why this exists
batchwatch measures how long jobs actually wait in LLM providers' async batch
queues. Batch is half price, but "done within 24 hours" cannot be planned
around, so most callers pay full price out of habit. This server puts the queue
evidence one tool-call away from the agent that is about to make that choice.