my-minimax-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@my-minimax-mcpgenerate a Python script to calculate fibonacci numbers"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
my-minimax-mcp
MCP server that wraps MiniMax AI as an autonomous code executor for Claude Code.
Purpose: Coding tasks consume the bulk of your Claude subscription quota on execution (writing, testing, debugging). This MCP server offloads that work to MiniMax API (~$0.04/task), so your Claude subscription handles significantly more tasks per day. Built-in savings tracking proves it with real data.
Architecture
Claude Code (Opus) ─── orchestrator
│
├── minimax_generate_code → simple code generation
├── minimax_agent_task → autonomous agent loop (read → write → test → debug)
├── minimax_chat → multi-turn conversation
├── minimax_plan → structured JSON implementation plan
├── minimax_cost_report → session cost tracking
├── minimax_session_tracker → cross-session usage tracking (auto-persist on shutdown)
├── minimax_web_search → web search via MiniMax Coding Plan API
└── minimax_understand_image → image analysis via MiniMax VLMThe key feature is the agent loop: MiniMax uses function calling to autonomously read files, write code, run tests, and debug — equivalent to a Sonnet sub-agent, but without consuming Claude subscription tokens.
Tools
Tool | Description | Default Model |
| Autonomous coding: read files, write code, run tests, debug loop. Supports tools: |
|
| Generate code, optionally write to file |
|
| Multi-turn conversation with context preservation |
|
| Structured implementation plan as JSON |
|
| Session token usage and cost breakdown | — |
| Cross-session usage tracking with self-improvement modes | — |
| Search the web using MiniMax AI | — |
| Analyze images using MiniMax VLM (JPEG/PNG/WebP, max 20MB) | — |
Installation
npm install my-minimax-mcpSetup
1. Get a MiniMax API Key
Sign up at platform.minimax.io and create an API key.
2. Install & Configure
Option A: Via npm (recommended)
npm install my-minimax-mcpOption B: From source
git clone https://github.com/wongo/my-minimax-mcp.git
cd my-minimax-mcp
npm install
npm run build3. Create .env
MINIMAX_API_KEY=your_api_key_here4. Register in Claude Code
claude mcp add --transport stdio --scope user minimax -- bash /path/to/my-minimax-mcp/run-mcp.shOr manually edit ~/.claude/settings.json:
{
"mcpServers": {
"minimax": {
"command": "npx",
"args": ["my-minimax-mcp"],
"env": {
"MINIMAX_API_KEY": "your-api-key",
"MINIMAX_DEFAULT_MODEL": "MiniMax-M2.7"
}
}
}
}Note: Use
claude mcp addfor the simplest setup, or edit~/.claude/settings.jsondirectly.
Restart Claude Code. The 8 tools will appear automatically. Verify with claude mcp list.
5. Enable Self-Improvement Loop (Optional)
npx my-minimax-mcp --initThis displays the CLAUDE.md template and creates the usage log. Copy the template to ~/.claude/CLAUDE.md to enable executor routing rules. Session tracking is automatic — the MCP server persists usage data on shutdown. See templates/setup-guide.md for details.
CLI (for debugging)
# Code generation
npx tsx src/cli.ts --task "fibonacci in Python" --language python
# Chat
npx tsx src/cli.ts --mode chat --task "explain async/await"
# Autonomous agent
npx tsx src/cli.ts --mode agent --task "fix the failing tests" --dir ./my-projectCLI runs also append to MINIMAX_COST_LOG, so --end-session and --savings-report include normal CLI usage in addition to MCP usage.
Configuration
All settings via environment variables:
Variable | Description | Default |
| API key (required) | — |
| Default model used by all MiniMax chat/plan/code/agent tools unless a per-call override is supplied |
|
| Agent loop max iterations |
|
| Per-task timeout |
|
| Additional allowed bash commands (comma-separated) | — |
| Base working directory for file operations; |
|
| Cost log file path |
|
| Session usage log path |
|
| Min MiniMax calls per session |
|
Self-Improvement Loop
Usage tracking is automatic — the MCP server persists session data to ~/.claude/minimax-usage.jsonl on shutdown (SIGTERM/SIGINT). No manual start/end calls required.
Optional commands via minimax_session_tracker:
"start"— check current mode and recent trends"status"— mid-session progress with trend analytics and streak info"end"— explicit close with root cause notes if target was missed
Modes:
Normal: Default. Target is
MINIMAX_SESSION_TARGETcalls (default: 5)Warning: Last session missed target — prioritize MiniMax
Forced: 2 consecutive misses — all code changes must use MiniMax
Trend analytics: The status command returns trend direction (improving/declining/stable), streak length, and actionable insights.
SessionEnd hook (optional, for fully automatic tracking):
npx my-minimax-mcp --end-sessionAdd to ~/.claude/settings.json hooks:
{
"hooks": {
"SessionEnd": [{
"hooks": [{
"type": "command",
"command": "npx my-minimax-mcp --end-session",
"timeout": 10
}]
}]
}
}Set MINIMAX_DEFAULT_MODEL to the highest model your Token Plan supports. All MiniMax tools inherit this value by default, and the API will reject models not available on your plan.
Failure Logging & Telemetry
Every tool call outcome (success, failure, retry) is automatically recorded to the logs/ directory — no configuration needed.
Log Files
File | Contents |
| Failure records (error category, fingerprint, caller project) |
| Success records (tool, duration, model, iterations) |
| Retry records (attempt count, final outcome) |
Files rotate monthly. The logs/ directory is gitignored.
Error Categories (8 types)
path_invalid · sandbox_violation · edit_file_no_match · iteration_limit · api_5xx · network_timeout · auth_error · unknown
Digest Analysis
# This month's digest (7 sections)
node scripts/analyze-failures.mjs
# Specific month
node scripts/analyze-failures.mjs --month 2026-05
# Custom date range
node scripts/analyze-failures.mjs --from 2026-05-01 --to 2026-05-15
# JSON output (for machine processing)
node scripts/analyze-failures.mjs --jsonOutput sections: Summary (total calls / success rate), Top categories, Top fingerprints (deduplicated bugs), Per-tool, Per-caller (which project called), Retry effectiveness, Quick wins (high-frequency issues with success rate < 80%).
Environment Variable Override
Variable | Description |
| Custom log directory (default: |
Token Savings Tracking
Every MiniMax call is tracked, and the savings are computed automatically. This includes normal CLI runs as well as MCP server usage. Use minimax_cost_report to see real-time savings per session, or run the CLI for cumulative reports.
Real-time (per session)
minimax_cost_report now includes a savings section:
tokensOffloaded: Exact count of tokens MiniMax handled instead of Claude
equivalentSonnetCalls: How many Sonnet sub-agent calls that represents
avgTokensPerCall: Self-adaptive metric (auto-improves with more data)
Cumulative (historical)
npx my-minimax-mcp --savings-reportShows all-time, monthly, and daily breakdowns with tool-level analysis:
=== MiniMax Token Savings Report ===
Tokens offloaded to MiniMax: 426,040 in + 161,496 out = 587,536 total
Equivalent Sonnet calls saved: ~68 (avg 8,635 tokens/call)
MiniMax API cost: $0.2468 (billed separately, not your subscription)
--- By Tool ---
agent_task 400,254 tokens (68.1%) | 8 calls
generate_code 144,290 tokens (24.6%) | 37 calls
chat 28,142 tokens (4.8%) | 20 callsSelf-Adaptive Accuracy
The avgTokensPerCall metric adapts to your usage patterns:
< 10 data points: Uses conservative default (8,000 tokens/call)
10-100 data points: Computes from all your metered calls
100+ data points: Uses rolling window of last 100 calls
Confidence level (LOW/MEDIUM/HIGH) is reported so you know how reliable the estimate is. The more you use MiniMax, the more accurate the savings report becomes.
Web Search & Image Understanding
These tools use MiniMax's Coding Plan API (separate from the chat completions endpoint). They are included in your Token Plan subscription at no additional per-call cost.
Web Search
minimax_web_search { query: "TypeScript MCP server tutorial" }Returns organic results (title, link, snippet, date) and related search suggestions.
Image Understanding
minimax_understand_image {
prompt: "Extract the business hours from this image",
imageSource: "https://example.com/schedule.png"
}Accepts three input types:
HTTP/HTTPS URL: Fetched and converted to base64 automatically
Local file path: Read from disk (supports
@prefix)Base64 data URL: Passed through directly
Supported formats: JPEG, PNG, WebP (max 20MB).
Features
Max output: 65,536 tokens per response (~10,000 Chinese characters / ~50K English words)
Think tag stripping: MiniMax
<think>...</think>reasoning tags are automatically removed from all responses
Security
The agent loop runs with strict sandboxing:
Bash whitelist: Only
npm test,npx,node,tsc,eslint,pytest,go test,cargo test, etc.Command chaining blocked:
&&,;,|operators are rejectedPath isolation: All file operations restricted to the working directory
Agent working-directory boundary:
minimax_agent_taskcan only operate insideMINIMAX_WORKING_DIRor one of its subdirectoriesIteration cap: 25 iterations max per task (configurable)
Timeout: 5 minutes per task (configurable)
Token budget: 500K input tokens max per task
Cost
MiniMax API pricing (per 1M tokens):
Model | Input | Output | Best for |
M2.5 | $0.118 | $0.99 | Routine code generation |
M2.7 | $0.30 | $1.20 | Complex reasoning |
Typical task cost: ~$0.04 (agent loop with 10 iterations).
Verified Test Results
Full integration test (14 MCP calls, 13 tests):
Total cost: $0.012 (1.2 cents)
Input tokens: 38,913
Output tokens: 7,228Test | Result |
API connectivity | PASS |
Code generation | PASS |
Agent loop (autonomous bug fix) | PASS |
Structured planning (JSON) | PASS |
Multi-turn conversation | PASS |
Cost tracking | PASS |
Multi-file task (todo module) | PASS |
Security (dangerous cmd blocked) | PASS |
Routing (Opus → MiniMax, not Sonnet) | PASS |
Graceful failure (max iterations) | PASS |
Web search (Japanese query) | PASS |
Image understanding (URL) | PASS |
Image understanding (local file) | PASS |
Testing
# Run all tests (148 tests)
npm test
# Run with coverage report
npm run coverageUnit tests cover safety validation, cost tracking, file writing, server initialization, session tracking, image utilities, the Coding Plan client, the savings calculator, and the failure logging system (error classification, secrets scrubbing, telemetry, retry tracking). Coverage report uses Node.js built-in test coverage (--experimental-test-coverage).
Project Structure
src/
├── mcp-server.ts # MCP server entry (stdio transport)
├── cli.ts # CLI for debugging
├── client/
│ ├── minimax-client.ts # OpenAI SDK wrapper for MiniMax chat API
│ ├── coding-plan-client.ts # Native fetch client for Coding Plan API (web search, VLM)
│ └── types.ts # Shared types and pricing
├── agent/
│ ├── loop.ts # Agent loop core logic
│ ├── functions.ts # Function definitions for MiniMax
│ ├── executor.ts # Function call executor
│ └── safety.ts # Whitelist, path validation, limits
├── tools/
│ ├── agent-task.ts # minimax_agent_task
│ ├── generate-code.ts # minimax_generate_code
│ ├── chat.ts # minimax_chat
│ ├── plan.ts # minimax_plan
│ ├── web-search.ts # minimax_web_search
│ ├── understand-image.ts # minimax_understand_image
│ └── index.ts # Tool registry
├── conversation/
│ └── store.ts # In-memory conversation store
└── utils/
├── cost-tracker.ts # Token usage and cost tracking (with session ID)
├── session-tracker.ts # Cross-session usage tracking and trend analytics
├── file-writer.ts # Safe file writing
├── image.ts # Image to base64 data URL conversion
├── savings-calculator.ts # Token savings computation (self-adaptive)
├── failure-logger.ts # Failure JSONL logging (scrubbing, fingerprints, monthly rotation)
├── telemetry.ts # Success / retry telemetry recording
├── error-classifier.ts # Error classification (8 categories)
├── secrets-scrubber.ts # Sensitive data redaction
└── retry.ts # Exponential backoff retry (with onAttempt callback)
scripts/
└── analyze-failures.mjs # Monthly failure & telemetry digest analyzer
logs/ # Runtime JSONL files (gitignored)Changelog
v1.5.0 (2026-05-24)
Observability improvements
analyze-failures.mjsre-classifies stored records at read time using current rules — historical logs update automatically when classifier patterns improveNew Section 8 "Re-classification Deltas" in digest output shows how many records were corrected vs. stored category
network_timeoutpattern extended to match"Request timed out."and"read timeout"variants (previously fell through tounknown)Retry telemetry now actually fires — all 5 tools (
web-search,chat,generate-code,understand-image,plan) passonAttempttowithRetry()and log failed attempts viatelemetry.recordRetry();retries-YYYY-MM.jsonlwill now have data
iteration_limit diagnostics
AgentTaskResultnow includesdiagnosticswhenreason === "iteration_limit": last 3 actions, unique files modified,stillProgressingheuristic, and a human-readable suggestion ("Retry with maxIterations=N" vs "decompose the task")filesChangedin iteration_limit returns is now populated from tracked writes instead of always being[]mcp-server.tswarns to stderr when caller setsmaxIterations < 10Iteration_limit failure log entries now include diagnostics payload for future analysis
Tests
161 tests (up from 152): 8 new
agent-looptests for diagnostic helpers, 1 safety regression test for cross-projectresolveWorkingDirectory
v1.4.0 (2026-05-17)
Failure Logging & Telemetry
Every tool call (success, failure, retry) is now recorded to monthly JSONL logs in
logs/8 error categories:
path_invalid,sandbox_violation,edit_file_no_match,iteration_limit,api_5xx,network_timeout,auth_error,unknownSecrets scrubbing — API keys, Bearer tokens, JWTs never reach logs
Deduplication fingerprints — identical bugs collapse into one entry
Per-caller attribution — failures attributed to the calling project by working directory
New
scripts/analyze-failures.mjsdigest with 7 sections: summary, categories, fingerprints, per-tool, per-caller, retry effectiveness, quick wins
Bug Fixes
Fixed
sandbox_violationnot being captured by failure logger (validation now inside try block)Fixed
callerProjectshowing as(unknown)for sandbox violations — falls back to raw input pathFixed
MINIMAX_WORKING_DIRdefaulting to minimax project dir, blocking all cross-projectagent_taskcalls;run-mcp.shnow sets it to~/Projects
Internals
retry.ts: addedonAttemptcallback for retry telemetryagent/loop.ts: addedreasonfield toAgentTaskResult(iteration_limit,timeout,task_complete,task_failed,no_tool_calls)148 tests (up from 96)
v1.3.8
Guaranteed
tokensOffloadedin every session cost reportAdded savings analyzer (
scripts/analyze-savings.mjs) with--diagnoseand date range flagsHardened launcher script; failure logging foundation
v1.3.6 – v1.3.7
edit_filefuzzy match (CRLF / trailing-space tolerant) with closest-3-lines hints on failureedit_file_batchfor atomic multi-point edits in a single iterationRouting calibration: raised Sonnet threshold from 5-file to cross-cutting refactor only
minimax_session_trackerauto-persists on shutdown (no manualendrequired)
License
MIT
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