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Ollama MCP Wrapper

Ollama MCP Wrapper

by PieterVDMerwe
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

generate_with_tools

Generate chat responses by giving the language model a list of tools it can invoke during the conversation.

Instructions

Execute chat generation with a list of tools exposed to the model.

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": {
      "model_name": "<model_name>",
      "messages": "<messages>",
      "tools": "<tools>"
    },
    "name": "generate_with_tools"
  }
}

Input Schema

NameRequiredDescriptionDefault
toolsYes
messagesYes
model_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden, but it only states the basic function. It does not disclose output format, side effects, authentication requirements, or any behavioral nuances.

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, direct sentence that immediately states the core purpose. Every word contributes to meaning, with no fluff or repetition.

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?

For a tool with three required parameters, no output schema, and no annotations, the description is far too sparse. It lacks essential details about expected response structure, tool format, or how it relates to sibling completion tools.

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

Parameters2/5

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

Schema description coverage is 0%, and the description does not compensate. It gives no explanation of model_name, messages, or tools beyond what the schema already shows, leaving the agent to infer their meanings.

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 action ('Execute chat generation') and the distinguishing feature ('with a list of tools exposed to the model'). This differentiates it from sibling tools like run_model_completion, which does not mention tool exposure.

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 guidance is provided on when to use this tool versus alternatives such as run_model_completion. There is no mention of appropriate scenarios, exclusions, or prerequisites.

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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