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FreeModel MCP

FreeModel MCP

by yummy342
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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freemodel_run

Run any task on a chosen AI model and platform using stored API keys. Set model, task, and optional parameters for tailored execution.

Instructions

Execute a task using a specific AI model from a specific platform. Uses your stored API keys.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "platform": "<platform>",
      "model": "<model>",
      "task": "<task>"
    },
    "name": "freemodel_run"
  }
}

Input Schema

NameRequiredDescriptionDefault
taskYesThe task to execute
modelYesModel e.g. "step-3.7-flash"
systemNoSystem prompt (optional)
platformYesPlatform ID: "stepfun","baidu","zhipu","aliyun","silicon","openrouter" etc.
max_tokensNoMax output tokens. Default varies by platform. Set 4000+ for reasoning models to prevent empty output.
temperatureNoTemperature (default 0.7)
reasoning_effortNoReasoning depth for step-3.7-flash. low=faster, high=deeper.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It mentions 'Uses your stored API keys,' which is useful, but does not disclose potential side effects (costs, API calls), return format, or any rate/timeout quirks. This is a significant gap for a tool that executes tasks.

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

Conciseness5/5

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

The description is a single, information-dense sentence. It front-loads the primary action and includes the key prerequisite (stored API keys), with no wasted words.

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

Completeness2/5

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

The tool has 7 parameters and no output schema, yet the description does not explain what the tool returns or any side effects. It also lacks information about when to adjust parameters like max_tokens or reasoning_effort. While the schema helps, the description alone is insufficient for an agent to fully anticipate the tool's behavior.

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 coverage is 100%, and each parameter has a descriptive comment (e.g., model, platform, max_tokens). The tool description adds no parameter information beyond the schema, so the baseline score of 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool's function with a specific verb ('Execute a task') and resource ('a specific AI model from a specific platform'). It distinguishes from sibling tools like freemodel_status or freemodel_models, which focus on health and listing, not execution.

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

Usage Guidelines4/5

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

The description implies when to use the tool by positioning it as the execution tool among siblings, but it does not explicitly mention alternatives or exclusions. The context is clear, but no direct 'use this when' guidance is provided.

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

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