Seven tools for running Tagsight extractions and pulling structured results from any MCP-compatible desktop client. Python pip install, API-key auth, same quota as the REST API.
Included on paid plans. Python 3.10+.pip install tagsight-mcp
export TAGSIGHT_API_KEY=ts_your_key
tagsight-mcpAdd this block to the MCP server config of the desktop client. The exact filename and location vary by client; consult the client's MCP settings docs for the path.
{
"mcpServers": {
"tagsight": {
"command": "tagsight-mcp",
"env": { "TAGSIGHT_API_KEY": "ts_your_key" }
}
}
}Each tool is a single MCP function the client invokes by name. Only extract_io_list consumes a credit; polling and read tools do not.
| Tool | Purpose | Credits |
|---|---|---|
extract_io_list | Start an extraction on a PDF or image. Returns a job_id. | 1 / call |
get_job_status | Poll extraction progress by job_id. | No |
get_job_results | Fetch the full structured output once extraction completes. | No |
list_jobs | List recent extractions for the authenticated account. | No |
get_io_summary | Signal-class counts (AI / AO / DI / DO) and BPCS / SIS split. | No |
search_instruments | Find tags across the account by pattern, signal class, or service. | No |
ask_tagsight | Ask a natural-language question against your extracted instrument data. | No |
Phrasings that work with most MCP-aware desktop clients. The client picks the appropriate tool from the catalogue and passes the parsed arguments to the server.
Extract the I/O list from ~/drawings/FS-101.pdf and give me the signal-class totals.Poll job_id abc123 until it completes, then summarise the instrument count by signal class.List my last ten extractions and pull the structured results for the most recent one.Run extractions for every PDF in ~/drawings/area-300 and keep the job_ids.Summarise the instrument count by signal class for the most recent extraction.An API key, the pip install, and a single MCP block in the client config. Same quota as the web app and the REST API.