llama-mcp-server

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llama_start

Launch a local llama-server instance as a child process using a specified GGUF model, with configurable port, context size, GPU layers, and CPU threads.

Instructions

Start llama-server as a child process with the specified 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": "<model>"
    },
    "name": "llama_start"
  }
}

Input Schema

Name	Required	Description
`model`	Yes	Path to GGUF model file
`port`	No	Port to listen on
`ctx_size`	No	Context size
`n_gpu_layers`	No	GPU layers (-1 = all)
`threads`	No	CPU threads

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Jun 12, 2026

TDQS

B3.2/5.0

Behavior2/5

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

No annotations provided. The description mentions 'as a child process' but does not specify blocking behavior, what happens if the server is already running, process management details, or resource implications.

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?

Single sentence with no unnecessary information. Efficiently conveys the core action and primary parameter.

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 that starts a server process, the description lacks crucial details: return value, success/failure indications, error conditions, runtime behavior, and interaction with other tools. Incomplete for an operation with 5 parameters and no output schema.

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?

All 5 parameters have descriptions in the schema (100% coverage). The tool description adds no additional meaning beyond the schema descriptions. Baseline 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 'Start llama-server as a child process with the specified model' clearly states the action (start), the resource (llama-server), and the key parameter (model). It distinguishes from siblings like llama_stop and llama_load_model.

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 on when to use this tool versus alternatives like llama_load_model or llama_stop. No context about prerequisites or when to avoid calling it.

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