mcp-mistral-queue

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An MCP (Model Context Protocol) server and CLI tool that coordinates local and multi-process / multi-client calls to the Mistral free tier (~1 request / 30 seconds) via a shared SQLite queue. It uses SQLite (WAL mode) and async queueing with a single in-flight task to space request starts. This is best-effort traffic control, not an official SLA.

Package: mcp-mistral-queue on PyPI · console script: mmq (not the package name) · current release: 0.1.1

Features

• Automatic rate-limit coordination: Shared ~31s start interval; on 429, shared backoff then re-enter the gate. Resets to the base interval on success.
• Multi-process & priority control: Multiple processes/tasks can enqueue work. Priority (1–3) plus single in-flight processing order the queue.
• Flexible model & message options: Any Mistral chat model name (defaults to mistral-small-latest; e.g. mistral-large-latest, codestral-latest), plus full conversation history via a messages array.
• Streaming & cancel handling: Streams the Mistral API response internally (tool returns the full text); on client cancel (CancelledError) updates task status in the DB.
• Local control DB: Temp DB under a per-user directory with mode 0700 (path overridable via MMQ_TEMP_DB_PATH).
• PyPI / uvx: Install once or run ephemerally; entry point is mmq.
• Mistral Vibe / Grok / Claude Desktop: Register as an MCP server (mmq --mcp). Do not use vibe mmq.py "..." — that runs Vibe’s agent CLI, not this tool.
• Good free-tier fit: Occasional jobs (e.g. translating docs) that can wait ~31s between calls without burning a dedicated rate-limit stack.

Prerequisites

• Python 3.10+
• uv recommended (uvx / uv run); pip also works
• A Mistral API key (MISTRAL_API_KEY)

export MISTRAL_API_KEY="your-mistral-api-key"

Install (PyPI)

Published and verified on PyPI.

# One-shot (no permanent install) — recommended for MCP hosts
uvx --from mcp-mistral-queue mmq --help

# Or install into an environment
uv pip install mcp-mistral-queue
# pip install mcp-mistral-queue

mmq --help

Quick smoke (needs MISTRAL_API_KEY; counts against free-tier quota):

uvx --from mcp-mistral-queue mmq "Reply with pong only."

Notes:

• Console script name is mmq. Wrong: uvx mcp-mistral-queue --mcp. Right: uvx --from mcp-mistral-queue mmq --mcp.
• Dependencies: mcp[cli]>=1.0.0,<2, mistralai>=1.0.0,<2 (pulled in by the package).

Usage

1. CLI mode

After PyPI install / via uvx, invoke mmq.
From a git checkout you can still use uv run mmq.py ... (PEP 723).

# Basic run (default model: mistral-small-latest)
uvx --from mcp-mistral-queue mmq "Explain Python list comprehensions briefly"
# or: mmq "Explain Python list comprehensions briefly"

# Choose a model (e.g. mistral-large-latest, codestral-latest)
mmq -m mistral-large-latest "Explain a complex algorithm"

# Custom system prompt
mmq -s "You are an AI that speaks casually." "How is the weather today?"

# Priority (1: high, 2: normal, 3: low)
mmq --priority 1 "Urgent question"

# Full conversation context as a messages JSON array
# (specify either prompt or --messages, not both)
mmq --messages '[{"role":"system","content":"Strict programmer"},{"role":"user","content":"What is ownership in Rust?"}]'

# Emergency brake: cancel queued / stuck work (no API call)
mmq --purge          # cancel all pending
mmq --purge-all      # cancel pending + processing
mmq --purge-id 42    # cancel one task by ID

2. MCP server mode (Vibe / Grok / Claude Desktop / …)

Expose ask_mistral and get_queue_status to MCP hosts.
Separate path from CLI prompts.

PyPI / uvx (recommended)

{
  "mcpServers": {
    "mistral-queue": {
      "command": "uvx",
      "args": ["--from", "mcp-mistral-queue", "mmq", "--mcp"],
      "env": {
        "MISTRAL_API_KEY": "your-mistral-api-key"
      }
    }
  }
}

If mmq is already on PATH (venv / uv pip install):

{
  "mcpServers": {
    "mistral-queue": {
      "command": "mmq",
      "args": ["--mcp"],
      "env": {
        "MISTRAL_API_KEY": "your-mistral-api-key"
      }
    }
  }
}

Local checkout (development)

{
  "mcpServers": {
    "mistral-queue": {
      "command": "uv",
      "args": [
        "run",
        "--with", "mcp[cli]>=1.0.0,<2",
        "--with", "mistralai>=1.0.0,<2",
        "--no-project",
        "/absolute/path/to/mmq.py",
        "--mcp"
      ],
      "env": {
        "MISTRAL_API_KEY": "your-mistral-api-key"
      }
    }
  }
}

After changing config, restart the client. Manual Vibe checklist: docs/SMOKE_VIBE.md.

3. Environment variables (optional)

Variable	Default	Purpose
MISTRAL_API_KEY	(required)	Mistral API key
MMQ_TEMP_DB_PATH	per-user under tempdir	Shared queue DB file path
MMQ_BASE_WAIT_TIME	31	Seconds between starts (free-tier pacing)
MMQ_DEFAULT_MODEL	mistral-small-latest	Default model name
MMQ_FAKE_API	off	Offline / e2e: fake client (1/true)

Other knobs (MMQ_MAX_WAIT_TIME, MMQ_MAX_RETRIES, …) exist for tuning; see mmq.py.

MCP tools

When the server is running, clients can use the following tools:

ask_mistral

Argument	Type	Default	Description
prompt	string	null	Single-shot user prompt text
messages	array	null	Conversation history ([{"role": "...", "content": "..."}])
model	string	"mistral-small-latest"	Mistral model name
system_prompt	string	null	Custom system prompt (only when using prompt)
priority	number	2	Task priority (1: high, 2: normal, 3: low)

get_queue_status

Returns current shared queue / rate-limit status as JSON:

Field	Type	Description
pending	number	Tasks waiting in the queue
processing	number	Tasks currently claimed / running
seconds_until_next_slot	number	Seconds until the shared API gate opens
current_wait_interval	number	Active shared wait interval (seconds)
in_flight	boolean	Whether any task is currently processing

Control data location

The coordination temp DB is stored in a per-user directory created with mode 0700:

• Default: <tempdir>/mcp_mistral_queue_<USER>/mcp_mistral_flow_control.db
  (tempfile.gettempdir(), often /tmp on Linux)
• Override: set MMQ_TEMP_DB_PATH to a full file path (parent dir is created with 0700)

Tests

# Unit + e2e (fake API; no network required)
uv run --with 'mcp[cli]>=1.0.0,<2' --with 'mistralai>=1.0.0,<2' \
  --with pytest --with pytest-asyncio --no-project \
  python -m pytest tests/ -v -m "not live"

# e2e only
uv run --with 'mcp[cli]>=1.0.0,<2' --with 'mistralai>=1.0.0,<2' \
  --with pytest --with pytest-asyncio --no-project \
  python -m pytest tests/e2e -v -m "not live"

# Live API (optional; consumes free-tier quota)
export MISTRAL_API_KEY=...
uv run --with 'mcp[cli]>=1.0.0,<2' --with 'mistralai>=1.0.0,<2' \
  --with pytest --with pytest-asyncio --no-project \
  python -m pytest tests/e2e/test_live_api.py -v -m live

e2e uses MMQ_FAKE_API=1 and a short MMQ_BASE_WAIT_TIME to exercise process boundaries (CLI / MCP stdio). For a manual Vibe UI check, see docs/SMOKE_VIBE.md.

Example: batch-style use of mmq (scripts/translate_readme.py)

Besides the CLI and MCP server, you can call the queue from Python. This repo ships a small sample:

scripts/translate_readme.py — regenerate locale READMEs from the English source via the same free-tier queue as mmq / ask_mistral.

Idea	Why it fits mmq
Occasional job	Docs change far less often than chat traffic
Can wait ~31s	ja then fr each take a gated slot
Shared DB	Does not bypass other free-tier clients on the machine
Programmatic API	Uses execute_mistral_queue_async + MistralRequest

Locales workflow: edit README.md (English) only; do not hand-maintain README.ja.md / README.fr.md.

export MISTRAL_API_KEY=...
# optional: TRANSLATE_MODEL=mistral-small-latest

# From a git checkout (imports mmq.py on PYTHONPATH via the script)
python scripts/translate_readme.py              # → README.ja.md + README.fr.md
python scripts/translate_readme.py --lang ja    # one language
python scripts/translate_readme.py --dry-run    # preview, no write

What the sample does:

1. Protects fenced code blocks (line FSM) and inline code with placeholders
2. Enqueues one translation job per language through execute_mistral_queue_async
3. Restores placeholders, fixes the language switcher, validates (e.g. balanced fences)
4. Writes outputs atomically

Use it as a template for other infrequent batch jobs (summaries, structured extraction) that should share the free-tier gate.

Further docs

• docs/SMOKE_VIBE.md — Vibe / MCP manual smoke
• docs/SEARCH_POSITIONING.md — where web search belongs (outside mmq base)
• docs/tasks.md — backlog
• docs/NOTES.md — design notes

License

MIT License

Copyright (c) 2026 utenadev