Clairic vs Reducto API + MCP

Clairic

Clairic's price is public at $0.10 per million input tokens with no output charge, and its docs publish JSON Schemas, limitations and when to use a decision model instead. It is a preview that Cloudflare calls an early checkpoint, served under an unversioned ID with no SLA, and its promised open weights have no date or licence.

Reducto API + MCP

Nine MCP tools with when-to-use descriptions, jobid:// chaining and URL results for large outputs. Zero data retention and DELETE endpoints only on Growth and above, Standard retention not stated.

Clairic

1. Send model as clairic in the body as well as in the URL. The input schema requires model and fields
2. Set reference_date, or add a line giving today's date to the state, for any field that depends on the current date
3. Treat a null value as not found, and read p_null, confidence or the 80% interval before acting. Typed output is well formed, not necessarily correct
4. Extract the inputs and do multi-step sums and table totals in code. Cloudflare says long arithmetic chains aren't reliable yet
5. Embed images as data URLs or base64 objects, at most four, 4 MiB each and 8 MiB in all. Remote image URLs are refused
6. Read the internal code on a 429. 3036 means the day's 10,000 free neurons are spent, 3040 means capacity, so retry later

Reducto API + MCP

1. Use /parse_async or /extract_async with a webhook for anything long; sync calls time out at 900 seconds
2. Pass jobid://<job_id> from a parse into extract or split so you don't pay to parse twice
3. Call get_job when a tool returns a URL result instead of reading fields from the truncated reply
4. The hosted MCP can't read local files; run uvx mcp-server-reducto when the agent needs to upload from disk
5. Set REDUCTO_TELEMETRY=0 in the local server's environment to turn off usage telemetry