Toolbox MCP
Enables name validation, arithmetic evaluation, shape identification from images, syllabus study material lookup, and graph-based route optimization with tolls.
README
Toolbox MCP
FastMCP implementation for the Toolbox challenge described in toolbox.txt.
Install
python -m pip install -e ".[dev]"
Run locally
python -m toolbox_mcp.server
The MCP endpoint is http://localhost:8000/mcp. Override HOST, PORT, or
MCP_PATH with environment variables when deploying.
The server exposes:
get_name(name)— validates and returns the supplied name.calculate(left, operator, right)— evaluates one supported arithmetic operation.identify_shape(image_base64)— identifies a PNG asrectangle,triangle, orcircle.list_study_materials()/fetch_study_material(document_id)— enumerate or read the Phase 2 syllabus.search_study_material(question)— return relevant syllabus passages within the recall budget.next_route_node(map_id, current, destination, visited, hops_remaining)— choose a least-cost graph hop using edge weights plus entered-node tolls.get_venues(day),get_schedule(person, day), andget_location(person, day)— fetch Phase 3 city data.find_meeting_window(...)— find the earliest clean window, with tentative inbox commitments as a fallback.plan_outing(...)— combine schedules, locations, venues, and grid travel into one outing answer.
Test
python -m pytest -q
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