LLM Chat MCP server

LLM Chat MCP server

Enables agents to inspect configured LLM models and send chat requests to them, with support for parameter overrides, file-based prompts, and output to files.

Category
访问服务器

README

llm-chat-mcp

MCP server for interacting with LLM models configured in Continue.dev's config.yaml.

What it does

Exposes 4 tools that let the agent inspect your configured models and send chat requests to them:

  • llm_chat_list_models — list all models in your config with their names and ids
  • llm_chat_get_model_params — inspect parameters (temperature, topP, etc.) for any model
  • llm_chat_get_model_prompt — read the system prompt configured for a model
  • llm_chat_send_request — chat with a model, optionally overriding parameters or loading prompts from files

Installation

pip install -e .

Or run directly from source without install.

CLI Usage

python -m llm_chat_mcp --default-model "GLM-5.2-FP8"
python -m llm_chat_mcp --config /path/to/config.yaml --default-model "ModelName"
python -m llm_chat_mcp --help
Argument Description Default
--config PATH Path to config.yaml ~/.continue/config.yaml
--default-model NAME Default model for send_request (none)
--timeout SECONDS Request timeout in seconds 19
--relative_paths_base PATH Base directory for resolving relative output file paths (process cwd)
--auto-output-dir PATH Directory for auto-generated output files when response exceeds auto_file_threshold and no output_file_path is set (OS temp directory)

Configuration

  • Config is re-read on every request — no restart needed
  • Auth uses apiKey from each model entry in config.yaml
  • If no model is specified (neither in CLI nor tool call), an error tells you how to set one

llm_chat_send_request parameters

The main tool. Sends a chat completion request to an LLM and returns the response.

Input parameters

Parameter Type Default Description
model_selector str (CLI default) Model name or id from config.yaml
prompt_text str (none) Prompt text to send
prompt_files list (none) List of file specs (string path or {path, start_line, end_line} dict)
include_line_numbers bool true Prefix each file line with N:
system_prompt str (from config) Override system message; "" suppresses entirely
temperature, topP, topK, minP float (from config) Sampling parameters
maxTokens, presencePenalty, frequencyPenalty int/float (from config) Generation parameters
extraParams dict (none) Extra body properties merged into API request
details bool false Include reasoning/thinking content in response
timeout float (CLI default) Per-request timeout override
output_file_path str (none) Write full response to this file (relative paths resolved against --relative_paths_base)
append bool false Append to output_file_path instead of overwriting; returns appended_line_start/appended_line_end
inline_preview_chars int 500 Max chars of content returned inline; preview applies only when a file is written
auto_file_threshold int 8000 Auto-write response to file when response_chars exceeds this and no output_file_path is set; 0 disables

Response structure

Always returned as JSON:

{
  "content": "<preview, full content, or empty>",
  "truncated": true,
  "metadata": {
    "model_name": "...",
    "model": "...",
    "elapsed_seconds": 1.23,
    "request_sent": {...},
    "response_headers": {...},
    "response_chars": 1234,
    "output_file": "...",
    "auto_output_file": "...",
    "created_dirs": [...],
    "appended_line_start": 201,
    "appended_line_end": 250
  }
}

Output strategy

The tool chooses one of three strategies based on parameters and response size:

  1. Explicit file (output_file_path set): full response written to the file. If append=true, the response is appended and appended_line_start/appended_line_end (1-based, inclusive) are returned so the caller can read only the appended slice via extract_lines.
  2. Auto file (no output_file_path, auto_file_threshold > 0, response_chars > threshold): full response written to an auto-generated file in --auto-output-dir (or OS temp). Filename format: llm_output_<YYYYMMDD_HHMMSS>_<6-char-uuid>.json.
  3. Inline only (no file written): full content returned in the content field.

Inline preview

When a file is written (explicit or auto), the content field contains a preview of the response:

  • If inline_preview_chars > 0 and len(content) > inline_preview_chars: truncated preview with suffix [truncated, full response in <file_path>].
  • If inline_preview_chars > 0 and len(content) <= inline_preview_chars: full content (fits in preview).
  • If inline_preview_chars == 0: empty content (file has the full response).

When no file is written, the full content is returned inline regardless of inline_preview_chars — this prevents data loss.

Continue.dev Integration

Add to .continue/mcpServers/llm-chat.yaml:

name: LLM Chat MCP server
version: 0.2.0
schema: v1
mcpServers:
  - name: LLM Chat MCP server
    command: python
    args:
      - "-m"
      - "llm_chat_mcp"
      - "--default-model"
      - "GLM-5.2-FP8"
      - "--timeout"
      - "570"
      - "--relative_paths_base"
      - "/path/to/your/workspace"
      - "--auto-output-dir"
      - "/path/to/your/workspace/.continue/skills/large-tasks/tmp-outputs"
    env:
      PYTHONPATH: "/path/to/llm-chat-mcp"

Then reload Continue.dev.

Project Structure

llm-chat-mcp/
├── pyproject.toml          # Dependencies: mcp, pyyaml, httpx
├── README.md               # This file
├── llm_chat_mcp/
│   ├── __init__.py
│   ├── __main__.py         # CLI entry point + tool registration
│   ├── config.py           # Config loading, model resolution
│   └── api.py              # API client, error handling
└── tests/
    └── test_output_strategies.py  # Tests for append, inline_preview, auto_file

Testing

python tests/test_output_strategies.py

Tests mock the API call and verify the file-writing and response assembly logic. Covers all combinations of output_file_path, append, inline_preview_chars, and auto_file_threshold.

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