This server provides AI-powered automation tools for generating, analyzing, and validating Git commit messages following the Conventional Commits specification.
generate_commit_message — Generate a structured conventional commit message from a plain-text description of changes, with auto-detection of commit type, scope, and breaking changes.
analyze_diff — Parse a raw git diff to produce a structured summary including files changed, lines added/deleted, and a suggested commit type.
suggest_type — Given a change description, suggest the best conventional commit type (e.g., feat, fix, chore) along with a confidence score.
validate_conventional — Validate an existing commit message against the Conventional Commits specification and report any issues or violations.
Notes:
All tools are stateless with no side effects.
Free tier allows 10 calls/day per tool; Pro tier is unlimited.
No authentication required for basic usage; a MEOK API key is needed for Pro/Enterprise tiers.
Commit Message MCP — automation tooling for commit message
Commit Message MCP — automation tooling for commit message. MIT.
# Install via pip
pip install commit_message_ai_mcp
# Or install via Smithery
npx -y @smithery/cli@latest install commit-message-ai-mcp --client claudeRelated MCP server: Git Helper AI MCP
MCP protocol compliant
Easy installation
Well-documented API
Production-ready
Active maintenance
This MCP server is built with EU AI Act compliance built-in:
✅ Article 9 — Risk Management System
✅ Article 13 — Transparency & Instructions for Use
✅ Article 15 — Bias Detection & Testing
✅ Article 26 — FRIA Support (where applicable)
✅ Article 50 — AI Content Watermarking (where applicable)
Need help getting compliant? Book a free 15-min diagnostic →
Need custom development, SLA guarantees, or white-label deployment?
Pro: $99/mo — Full MCP suite + EU AI Act tracking
Enterprise: $499/mo — Custom dev + SLA + Dedicated support
View Pricing → | Contact Sales →
This server is part of the MEOK AI Labs ecosystem — 300+ MCP servers for sovereign AI governance.
Domain | Purpose |
EU AI Act compliance marketplace | |
AI safety & monitoring | |
Sovereign AI platform | |
Legacy modernization |
MIT © CSOAI-ORG
Build something that touches users? You need compliance. MEOK ships 38 governance MCPs that drop in alongside this tool — EU AI Act, DORA, NIS2, CRA, GDPR, ISO 42001, FDA SaMD, MDR, Basel, MiFID II, MiCA, COPPA, and more.
# One-shot install of the governance pack
npx meok-setup --pack governanceFree tier: 10 calls/day per MCP. Pro tier (£79/mo): unlimited + cryptographically signed compliance attestations your auditor verifies independently.
→ Full catalogue: councilof.ai/catalogue → MEOK AI Labs: meok.ai
Tier | Price | What you get | Stripe |
Smoke test | £1 | Signed sample MCP-Hardening report + Article 50 PDF | |
Quick Kit | £9 | EU AI Act Article 50 implementation guide (C2PA + EU-Icon) | |
Founder Call | £29 | 30-min 1-on-1 with the founder |
Refundable. UK Stripe — VAT-clean. Builds on the 81-MCP MEOK fleet. Verify any signed report at https://meok.ai/verify.
Add to your claude_desktop_config.json (Claude Desktop) or your MCP client config:
{
"mcpServers": {
"commit-message-ai-mcp": {
"command": "uvx",
"args": ["commit-message-ai-mcp"]
}
}
}Or: pip install commit-message-ai-mcp then run the commit-message-ai-mcp command (stdio transport).
Once configured, ask your assistant, for example:
"Use generate_commit_message to …"
"Use analyze_diff to …"
"Use suggest_type to …"
Parse a git diff and produce a structured summary with files changed, additions, deletions, and suggested commit type.
Behavior: This tool generates structured output without modifying external systems. Output is deterministic for identical inputs. No side effects. Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.
When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.
When NOT to use: Not suitable for real-time production decision-making without human review of results.
Args: diff_text (str): The diff text to analyze or process. api_key (str): The api key to analyze or process.
Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.
| Name | Required | Description | Default |
|---|---|---|---|
| diff_text | Yes | ||
| api_key | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description excels by covering side effects (read-only, no external modifications), authentication (none for basic, API key for pro), rate limits (10/day free, unlimited pro with header details), error handling (structured errors), idempotency (fully idempotent), and data privacy (no storage/logging). This is exceptionally thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Behavior, When to use, When NOT to use, Args, Behavioral Transparency). The purpose is front-loaded. However, there is some redundancy between the 'Behavior' and 'Behavioral Transparency' sections, making it slightly less concise than ideal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, 1 required), the presence of an output schema (so return values are covered), and the comprehensive behavioral transparency section, the description is nearly complete. It covers purpose, usage, side effects, auth, rate limits, error handling, idempotency, and privacy, leaving no major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters in the 'Args' section but only repeats names and types without adding meaningful semantics. The main description clarifies diff_text's purpose, and api_key is partly explained in the Behavioral Transparency section. Overall, compensation is partial but not complete, warranting a 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it parses a git diff and produces a structured summary with specific outputs (files changed, additions, deletions, suggested commit type). The 'When to use' section is generic and does not explicitly distinguish from sibling tools like suggest_type, which also deals with commit types, but the main purpose is well-defined with a specific verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes explicit 'When to use' and 'When NOT to use' sections, providing guidance on appropriate contexts and cautioning against real-time production use without human review. However, it does not mention alternatives or explicitly contrast with sibling tools, so a 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate a conventional commit message from a description. Auto-detects type, scope, and breaking changes.
Behavior: This tool generates structured output without modifying external systems. Output is deterministic for identical inputs. No side effects. Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.
When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.
When NOT to use: Not suitable for real-time production decision-making without human review of results.
Args: changes_description (str): The changes description to analyze or process. commit_type (str): The commit type to analyze or process. scope (str): The scope to analyze or process. breaking (bool): The breaking to analyze or process. api_key (str): The api key to analyze or process.
Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.
| Name | Required | Description | Default |
|---|---|---|---|
| changes_description | Yes | ||
| commit_type | No | auto | |
| scope | No | ||
| breaking | No | ||
| api_key | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It includes a dedicated 'Behavioral Transparency' section covering read-only operation, no side effects, deterministic output, rate limits, error handling, idempotency, and data privacy. This is comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized with sections and bullet points, but contains redundancy (e.g., 'Behavior' paragraph overlaps with 'Behavioral Transparency') and a verbose 'Args' section that provides no useful information. Could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The behavioral aspects are well-covered, but the lack of parameter explanation is a significant gap. The output schema exists, so return value details are not required, but the description could mention the output format. Overall, incomplete due to poor parameter semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The 'Args' section merely restates parameter names and types without adding meaning (e.g., 'changes_description (str): The changes description to analyze or process.'). This adds no value over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a conventional commit message from a description, with auto-detection of type, scope, and breaking changes. This distinguishes it from siblings like 'analyze_diff' or 'suggest_type'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes explicit 'When to use' and 'When NOT to use' sections, advising use for structured analysis and cautioning against production use without human review. However, it does not directly compare to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Suggest the best conventional commit type for a change description with confidence scoring.
Behavior: This tool is read-only and stateless — it produces analysis output without modifying any external systems, databases, or files. Safe to call repeatedly with identical inputs (idempotent). Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.
When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.
When NOT to use: Not suitable for real-time production decision-making without human review of results.
Args: description (str): The description to analyze or process. api_key (str): The api key to analyze or process.
Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.
| Name | Required | Description | Default |
|---|---|---|---|
| description | Yes | ||
| api_key | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden and excels: it declares read-only, stateless, idempotent, no side effects, authentication requirements (none for basic, key for Pro), rate limits (10/day free, unlimited Pro), error handling (structured errors), and data privacy. This comprehensive disclosure exceeds typical requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with labeled sections but excessively verbose. The 'Behavioral Transparency' section repeats information from earlier 'Behavior' section. Approximately 50% of the text could be trimmed without losing meaning, making it less efficient for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description appropriately avoids detailing return values. It covers purpose, usage, parameters, and extensive behavioral details. Minor gap: rate limits and authentication details are split between sections. Still, it provides a complete picture for a tool of moderate complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The 'Args' section provides minimal descriptions: 'description (str): The description to analyze or process' and 'api_key (str): The api key to analyze or process.' Given 0% schema description coverage, these are insufficient—they don't clarify expected format, how the key is used, or that Pro requires an environment variable (not the parameter). The parameter meaning is ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states: 'Suggest the best conventional commit type for a change description with confidence scoring.' This distinctively identifies the tool's purpose and differentiates it from siblings like analyze_diff, generate_commit_message, and validate_conventional, which cover other aspects of commit analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'When to use' and 'When NOT to use' sections, providing context: use for structured analysis/classification, not for real-time production decisions without human review. However, it does not explicitly contrast with siblings, leaving some ambiguity about when to prefer this over analyze_diff or validate_conventional.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Validate a commit message against the Conventional Commits specification and report issues.
Behavior: This tool is read-only and stateless — it produces analysis output without modifying any external systems, databases, or files. Safe to call repeatedly with identical inputs (idempotent). Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.
When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.
When NOT to use: Not suitable for real-time production decision-making without human review of results.
Args: message (str): The message to analyze or process. api_key (str): The api key to analyze or process.
Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | ||
| api_key | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and excels: details side effects (none), authentication, rate limits, error handling, idempotency, and data privacy. This is comprehensive and meets the highest standard.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections, but repetitive (e.g., Behavior and Behavioral Transparency overlap). Could be more concise while retaining completeness. Still, it is organized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, description covers purpose, usage, behavior, and parameters adequately. No major gaps. Could mention expected output format briefly, but output schema presumably handles that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. The Args section is minimal: 'message: The message to analyze or process.' and 'api_key: The api key to analyze or process.' Adds little beyond the parameter names. No format, constraints, or defaults explained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates commit messages against the Conventional Commits spec. It specifies the verb (validate) and resource (commit message) and reports issues. However, it does not explicitly differentiate from sibling tools like analyze_diff or generate_commit_message, though the purpose is distinct enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit 'When to use' and 'When NOT to use' sections, advising use for structured analysis against standards and cautioning against real-time production decisions without human review. Lacks reference to alternative tools but gives good context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0analyze_diffgenerate_commit_messagesuggest_typevalidate_conventionalTools have distinct inputs and outputs: analyze_diff for diffs, generate_commit_message for descriptions, suggest_type for type suggestions, validate_conventional for message validation. Some overlap in type suggestion but descriptions clarify use cases.
Three tools follow verb_noun pattern (analyze_diff, generate_commit_message, suggest_type). validate_conventional is slightly inconsistent as 'conventional' is an adjective rather than a noun, but the pattern is still clear.
4 tools is appropriate for a focused commit message assistant, covering analysis, generation, suggestion, and validation without being too few or too many.
Covers core conventional commit workflows well. Missing explicit tool to generate message from diff (though chainable) and maybe a parser, but overall surface is solid.
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