specir-mcp
Enables turning technical documents into a structured intermediate representation (SpecIR) and querying it via five MCP tools: specir_resolve, specir_fetch, specir_explain, specir_search, and specir_status. It provides a standardized way to extract, store, and retrieve document sections, tables, figures, entities, and provenance.
README
specir-mcp
specir-mcp is a data-neutral framework for turning technical documents into
a structured intermediate representation (SpecIR) and querying it through five
stable MCP tools.
The repository contains no standards PDFs, extracted specification text, knowledge-base databases, model weights, or vendor-specific protocol tables. All bundled demo content is fictional.
Features
- Document, section, table, figure, entity, passage, provenance, and edge IR.
- Extensible domain plugin manifests with dependency-aware loading.
- PDF outline-based section extraction and reusable structure parsers.
- SQLite-backed exact lookup, fetch, explanation, search, and status APIs.
- A five-tool FastMCP surface:
specir_resolve,specir_fetch,specir_explain,specir_search, andspecir_status. - Explicit coverage metadata so missing extraction is not confused with absence from a source document.
Quick start
python -m venv .venv
. .venv/bin/activate
pip install -e ".[test]"
# Generate a small database from the fictional Acme Device Interface fixture.
specir-demo --output data/demo.db
export SPEC_IR_DB="$PWD/data/demo.db"
specir-mcp-server
The same server may be launched from a source checkout:
fastmcp run src/specir/query/server.py
Example MCP calls:
specir_resolve(kind="command", id="A1h", spec="acme-device")
specir_fetch(uid="acme-device:2.1", include_xrefs=true)
specir_explain(name="Read Telemetry", kind="command", spec="acme-device")
specir_search(query="telemetry", spec="acme-device")
specir_status()
When a database contains one document, spec="auto" selects it. With multiple
documents, exact lookups return candidates and request an explicit spec.
Using your own data
Create a database with specir.query.schema.create_database, then insert
documents and entities using the schema documented by the Python dataclasses.
Set SPEC_IR_DB to that database before starting the server. The framework
never downloads or bundles source documents.
The optional PDF extractor can build coordinate-clipped section records:
from specir.extractors.pdf import build_section_tree
sections = build_section_tree("my-spec", "path/to/your-document.pdf")
You are responsible for having permission to process and store the documents you supply.
Development
pytest
python -m build
The tests create temporary synthetic databases and do not require external specifications or network access.
License
Apache License 2.0. See LICENSE.
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