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m2mfreedom

freedom-m2m-mcp-server

Official

freedom_python_sandbox

Execute deterministic Python math, financial, and statistical expressions in an isolated AST-validated sandbox for safe, verifiable computation.

Instructions

Isolated AST Python Math & Quantitative Sandbox (60 Sats / ~$0.057 USDC | 100/100 SLA Guaranteed). Executes deterministic math, financial, and statistical Python expressions inside a strict AST-validated sandbox. Protected by HTTP 402 (L402 / x402).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesPython math/statistical code to execute (e.g., "print(round(sum([10.5, 20.3, 45.1]) * 1.16, 4))").
authHeaderNoOptional payment proof header: "L402 <macaroon>:<preimage>" or "x402 base:<0xTxHash>" or "x402 solana:<TxSignature>".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

B3.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It does disclose real behavioral traits: AST-validated strict sandbox, determinism, and HTTP 402 payment gating with L402/x402 proof. It omits execution limits, allowed/blocked operations, timeout, and failure modes, leaving important runtime behavior undisclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core capability, then execution model, then payment note. Efficient overall, but the parenthetical price and '100/100 SLA Guaranteed' are promotional filler rather than decision-relevant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter tool with no output schema, the definition should say what comes back (stdout only? structured value? error format), given 'print(...)' is the example. Payment gating is covered, return semantics are not, leaving a meaningful gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and both parameters are documented inline (code example, payment header formats), so the schema does the heavy lifting. The description only echoes the sandbox context and adds no further parameter semantics; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: executes deterministic math/financial/statistical Python expressions in an AST-validated sandbox. That distinguishes it from siblings like freedom_clean_scraper or freedom_agent_memory, though the marketing framing ('Freedom', pricing, SLA) dilutes the core statement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance relative to alternatives, no statement of what the sandbox cannot do (imports, network, file access, timeouts). The payment notice implies a precondition but never explains the intended use case or boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.