Statemind MCP server

• Registry nameai.statemind/python-code-validatorverified in the MCP registry

The registry name sits under statemind.ai. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.

• Stateanswerschecked 2026-10-23
• Tools3
• Server calls itselfpython-code-validator
• Server version1.29.0
• Protocol version2025-06-18

On 2026-10-23 the server answered initialize and tools/list without a sign-in. First answer in 670 ms.

• Its tools do verify AI-generated code by parsing and running it, but not score voyage risk and compare diversion costs; track fleet ship positions with signal age shown.
• Checked on 3 of the 7 days it takes to judge reliability.

Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.

• INITE MCP scoreafter a weeka score needs 7 daily checks: 3 so far
• What an agent can do with it1 of 3 use cases
• Answeredmeasuring3 of the 7 daily checks it takes to print a share
• Median first answer626 ms
• Space in an agent's context≈ 4,655 tokensthe definitions of all its tools (3), which an agent carries on every turn
• Tool definitionsA · 100 of 100
• Typed results3 of 3 toolsdeclared outputSchema: results come typed, read once

• Every tool passes all six checks.

A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →

• validate_python

  Check Python source without running it: parse, lint (ruff), type-check (mypy), AST security policy, credential scan. Safe on code you do not trust. Use it on every Python file you generated or edited, before writing it to disk…

• repair_python

  Everything validation does, plus deterministic fixes: the corrected source comes back in fixed_code, and the original is kept whenever the fix cannot be proven safe. The code is still never run. Use it when validation failed and you want…

• execute_python

  Everything repair does, and then RUNS the code in a throwaway container — no network, read-only filesystem, killed at options.timeout_s — reporting exit code, stdout and stderr. Any '>>>' examples in the code are run too, and one that…