Grant Tools

A community-built grant research assistant adapted from DaedalMap's Research MCP. Install it from this repository, connect an MCP client, and describe a project. Grant Tools works through the pre-submission phases: finding programs that fit, checking eligibility and blockers, pulling precedent from past awards, shortlisting, and helping with memos, budgets, and submission checklists. It never estimates odds of winning and does not handle post-award reporting.

Coverage: every country runs the same workflow, and each country's backend declares what it can do. US supports everything: discovery, precedent, readiness scoring, memos, budget frameworks, writing templates, and live open-opportunity checks. Canada supports discovery, precedent for every shortlisted program, and program-page links for open status (labelled unverified). A request a country cannot serve comes back as a named capability_gaps entry, never as an empty result.

What it is built for

Grant Tools was built for disaster recovery, hazard mitigation, community resilience, and climate adaptation work, and its curated program catalogs show it. These catalogs are what the shortlist ranks: a program has to be in one to be matched, checked for eligibility and blockers, and scored.

Counts are programs carrying each tag (a program can carry several), as of October 2026.

The data underneath is broader than the catalogs. USAspending, NSF, NIH, and Grants.gov (every posted and forecasted opportunity) cover all US federal programs, and Canada's Grants and Contributions disclosure and the Tri-Agency award tables cover all Canadian federal programs. A project outside the focus areas still runs, but expect a short shortlist: the funders are in the data, the programs are not yet in a catalog. Adding them is the program import pipeline, and validate_program.py checks a new row.

Place handling uses DaedalMap loc_ids (stable identifiers for counties, states, provinces, and other places). Grant Tools calls DaedalMap's hosted geometry MCP to turn place text into loc_ids by default. You can supply a loc_id directly, or point GEOMETRY_MCP_URL at a local geometry server.

Related MCP server: US Federal Procurement MCP

Quickstart

1. Get the code and install. Python 3.11 or newer. From the repository folder:

   py -m venv .venv
   .\.venv\Scripts\python -m pip install -r requirements.txt

2. Get the data for your country. Open the Grant Tools download page and choose the USA or Canada grant data bundle. Review its size, coverage, sources, and checksum before confirming the download. Unzip the bundle into this repository's data/ folder so the result contains data/countries/. You may unzip both into the same data/ folder. Each ZIP also includes source details and checksums in countries/<USA|CAN>/grant_data_manifest.json. /health on the running server shows which bundles are installed and whether this code version can read them. You can build tables from upstream sources with the pipeline below.

3. Configure only if needed. data/ is the default. If you unzipped the bundle elsewhere, copy .env.example to .env and set GRANT_DATA_ROOT to the folder containing countries/.

4. Start the server.

   .\.venv\Scripts\python server.py

5. Connect your MCP client to http://127.0.0.1:7020/mcp. For Claude Code:

   claude mcp add --transport http grants http://127.0.0.1:7020/mcp

   Then describe your project. The first tool, grant_intake_or_update_project, takes it from there.

Configuration

Settings come from environment variables or a .env file next to the code.

Place lookups

The grant tools need one thing from DaedalMap: turning place text (a county, state, ZIP code, province, or municipality) into a loc_id. They call the geometry tool convert_reference at GEOMETRY_MCP_URL, DaedalMap's hosted MCP by default. No setup or account is needed; a grant session makes only a few lookups, well inside the free anonymous allowance. You can also pass a loc_id directly in place of place text.

Include the parent region for names that repeat: "Washington County, Oregon", "Prince George, British Columbia". When a name is ambiguous or not found, intake says so in notes and unresolved_places, with candidate loc_ids where the geometry tools returned them.

Data

The tools read processed tables from GRANT_DATA_ROOT. Downloaded ZIPs provide ready-to-use snapshots. The included pipeline can build your own tables under data/ from official upstream sources. Collector output goes to state/ and adds recent announcement leads; it does not replace historical award tables.

For example, build California opportunities and awards yourself:

.\.venv\Scripts\python pipeline\downloaders\download_california_grants_portal.py
.\.venv\Scripts\python pipeline\converters\convert_california_grants_portal.py

Each source has its own downloader and converter. Some upstream files are large and take time to fetch. Run only the sources you need; their outputs use the same data/countries/ layout as the downloadable bundles.

Announcement collectors

The included ARC, California, Canada, and US State Department collectors can run independently of the historical pipeline. List them, probe feeds without writing, and then run the ones you want:

.\.venv\Scripts\python collectors\run_all.py --list
.\.venv\Scripts\python collectors\run_all.py --only arc,california --probe
.\.venv\Scripts\python collectors\run_all.py --only arc,california

To keep that selection, set GRANT_COLLECTORS=arc,california in .env and run collectors/run_all.py without --only. The command runs once. Schedule it daily with Task Scheduler or cron for ongoing checks. Use GRANT_COLLECTORS=none to disable scheduled polls. Each collector also runs on its own (python collectors\arc_grant_announcements.py) and supports --probe. The collectors need no API keys. Their snapshots go to GRANT_STATE_DIR.

Phase 1 reads the snapshots that apply to the project (ARC for Appalachia, California for California, Canada for Canadian projects, State Department for international work) and returns only leads about the project's sectors and place in regional_evidence. When a feed has funding news but none of it fits, the result says so (relevance_note) rather than listing unrelated items.

"Is this program open right now?" asks Grants.gov live for US federal programs. The shortlist's open status comes from the bundle's opportunity snapshot and is labelled checked_snapshot; programs without a Grants.gov code (state programs, Canada) return their official program page to check.

Sources

Cite the original sources when you use their data.

The code is available under the MIT License. Country bundles and upstream source records retain their respective source terms; see each bundle's grant_data_manifest.json for provenance.

Tools

Layout

Docs

• docs/grant_mcp_quickstart.md - the tool workflow once connected

• docs/grant_mcp_mode.md - product shape and method

• docs/program_import_pipeline.md - how to add a program so the tools use it correctly; validate_program.py checks it

• docs/proposal_section_model.md - the proposal section vocabulary and how per-funder requirements resolve

• docs/grant_collectors.md - how to add sources and collectors

• docs/grant_source_matrix.md - source inventory by evidence layer

• docs/future_data_import.md - candidate data sources not yet imported, and their status