llama-mcp-server

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llama_complete

Generates text completions from a prompt with adjustable parameters for max tokens, temperature, top-p, top-k, stop sequences, and seed.

Instructions

Generate text completion from a prompt

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": {
      "prompt": "<prompt>"
    },
    "name": "llama_complete"
  }
}

Input Schema

Name	Required	Description
`prompt`	Yes	The prompt to complete
`max_tokens`	No	Maximum tokens to generate
`temperature`	No	Sampling temperature (0-2)
`top_p`	No	Nucleus sampling threshold
`top_k`	No	Top-k sampling
`stop`	No	Stop sequences
`seed`	No	Random seed for reproducibility

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Jun 12, 2026

TDQS

B3.1/5.0

Behavior2/5

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

The description lacks any behavioral details beyond the basic purpose. It does not mention side effects, prerequisites (like a loaded model), or whether calls are blocking/streaming. With no annotations provided, the description should compensate.

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 sentence, front-loaded with the verb 'Generate', and contains no unnecessary words. It is appropriately sized for its simplicity.

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?

The description is adequate for a basic text completion tool, but it omits important context: no mention of required model loading, no output format description (though no output schema exists), and no explanation of how this differs from similar tools. With 7 parameters and no annotations, it could be more complete.

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?

The input schema has 100% parameter description coverage, so the schema already explains all parameters. The description adds no additional information about semantics, but the schema is sufficient.

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?

The description 'Generate text completion from a prompt' clearly states the tool's purpose with a specific verb ('Generate') and resource ('text completion'). It distinguishes from siblings like 'llama_chat' and 'llama_infill', but could be more precise about requiring a loaded 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. For example, it doesn't explain the difference between 'llama_complete' and 'llama_chat' for conversational text generation.

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