MCP Tool Discovery Workbench · AI Engineering

A scoped MCP inventory server that discovers schemas inside a measured context budget.

Python 3.10+, Node 22.18+, dictionaries, JSON-RPC request ids, stdin/stdout and child processes. The core uses standard libraries. The grader checks your selected workspace; it never fills in missing behavior from the reference.

Build and run your version

From the repository root, initialize once. A fresh starter fails intentionally.

bash

python3 scripts/project_test.py mcp-at-scale --init learning-artifacts/mcp-at-scale
python3 scripts/project_test.py mcp-at-scale --stage 1 --path learning-artifacts/mcp-at-scale --strict

Implement each stage, then run the cumulative grader and the supplied input driver:

bash

python3 scripts/project_test.py mcp-at-scale --all --path learning-artifacts/mcp-at-scale --strict
cd learning-artifacts/mcp-at-scale
python3 cli.py samples/inventory.json --query "pods count" --max-chars 500

The driver and offline samples are provided scaffolding. Its imports resolve to your implementation. Public input types and function signatures live in the starter and API contract.

Inspect the reference separately

From the repository root:

bash

python3 scripts/project_test.py mcp-at-scale --all --solution --strict
cd projects/mcp-at-scale/solution
python3 cli.py samples/inventory.json --query "pods count" --max-chars 500

Observe the change

The file supplies three resource families, exposing fifteen read tools plus catalog_search. Search returns the best matching schema within the exact serialized tools-array budget. The exhaustive teaching registry remains 250 tools.

Edit a copy of the sample and rerun the command. Keep the input beside the output so someone else can reproduce the result; the supplied samples are authored teaching data.

Integration and limits

Run python3 cli.py /absolute/inventory.json --serve as a stdio server. tools/call catalog_search takes query, max_chars and k; the response returns selected public schemas and their character count.

The stdio transport implements the documented 2025-06-18 and 2025-11-25 initialization/tools subset. It is not a claim of full current MCP conformance. Inventory reads are local recordings; the generated tool count is not 250 distinct integrations.

Stages

Primary references

Optional standard MCP client verification

The optional track uses mcp==2.1.1, the installed official Python client, against this project's actual stdio process. It negotiates the declared 2025-11-25 legacy tools contract. This does not establish support for every newer protocol feature.

bash

python3 -m venv .venv-mcp
.venv-mcp/bin/python -m pip install -r projects/mcp-at-scale/requirements-framework.txt
.venv-mcp/bin/python scripts/project_test.py mcp-at-scale --all --solution --optional --strict

Use --path learning-artifacts/mcp-at-scale to run the same client against your implementation. The default track stays standard-library-only; missing optional packages produce SKIP, which fails strict optional grading.

Import a small REST contract

rest_adapter.py imports OpenAPI 3 GET operations with unique operationId and primitive path/query parameters. Unsupported parameter forms fail explicitly; write operations are excluded. Each imported operation retains the canonical source-spec SHA-256.

bash

python3 cli.py samples/api-recordings.json --openapi samples/api.json --query "incident" --max-chars 800
python3 cli.py samples/api-recordings.json --openapi samples/api.json --serve

Call incident_get with {"id":"checkout-1"}. The authored recording must match the supplied arguments; a different id is rejected instead of receiving a misleading canned answer. --base-url http://127.0.0.1:PORT explicitly enables actual GETs against your loopback fixture. Redirects and non-loopback endpoints are rejected, requests time out after five seconds and response bytes are capped at one megabyte. This narrow importer does not promise full OpenAPI coverage.