patchwork-mcp-server

by higebu

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct operation: lookup by message ID, get patch details, get series, get comments, get checks, list projects, list recent series, and search patches. No two tools have overlapping purposes.
Naming Consistency4/5
Tools mostly follow a verb_object pattern with underscores (e.g., get_patch, list_projects). 'recent_series' deviates slightly as adjective_object, but overall style is consistent and clear.
Tool Count5/5
With 8 tools, the server covers core interactions without being too sparse or overwhelming. Each tool serves a clear need within the Patchwork domain.
Completeness4/5
The set covers essential read operations: project listing, patch/series retrieval, comments, checks, and search. Missing creation or modification tools, but that aligns with a read-focused MCP server.
Average 3.5/5 across 8 of 8 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on May 11, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description is the sole source of behavioral info. It does not disclose side effects, authentication needs, rate limits, or specifics beyond the return fields. The read operation is implied but not explicitly stated as non-destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) with no wasted words. However, it omits important details, making it borderline under-specified. Conciseness slightly suffers from insufficient content.
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?
Given the tool's simplicity (single parameter, no output schema), the description covers the basic purpose and output fields. However, it lacks completeness in parameter explanation and usage context, leaving gaps for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no context about the required parameter 'patch_id'. It does not explain what a patch_id is, how to obtain it, or its format. The description fails to compensate for the schema's lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Get), the resource (a single patch), and specifies included fields (submitter, delegate, state, tags, check summary). It effectively differentiates from sibling tools like search_patches (search) and list_projects (list).
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 is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context for use, or exclusion criteria. The agent receives no direction for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'cover letters' but the tool name is 'recent_series', which may confuse. It explains collapse_revisions behavior but lacks details on ordering, recency criteria, and pagination despite having a limit parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff, concise and to the point. Could be slightly more structured (e.g., separating purpose from collapse_revisions behavior), but efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters and an output schema, the description lacks details on what is returned (cover letters vs series), ordering, pagination behavior, and response structure beyond what the schema provides. Incomplete for agent decision-making.
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?
Schema coverage is 75% (three of four parameters have descriptions). The description adds value by explaining collapse_revisions beyond its schema description, but does not explain the limit parameter, which has no schema description.
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 clearly states 'List recent cover letters on a project', specifying verb, resource, and optional filter. However, it does not differentiate from sibling tools like get_series or search_patches.
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 vs alternatives. For example, it does not mention that get_series is for a specific series or that search_patches is for broader searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It mentions 'time-ordered' but lacks details on read-only nature, auth requirements, rate limits, pagination, or empty results handling. With 0 annotations, this is insufficient.
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?
A single sentence that front-loads the core purpose with no wasted words. It is the ideal conciseness for a simple tool.
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 covers the basic functionality and ordering, but lacks usage guidance and behavioral transparency. With an output schema, return values are covered, but overall completeness is adequate with clear gaps.
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?
Schema description coverage is 100%, so the schema already explains each parameter. The description adds 'time-ordered' which relates to output ordering, not parameter semantics. Since coverage is high, baseline 3 is appropriate.
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 clearly states the verb 'Get' and the resource 'comment thread on a cover letter or a patch', and adds ordering behavior. It is distinct from siblings like get_patch or get_series, but does not explicitly differentiate from sibling tools.
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 like get_patch or search_patches. The description does not provide context for when comment retrieval is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose behavioral traits such as required permissions, rate limits, or non-obvious side effects. The description alone lacks transparency for responsible selection.
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?
Two concise sentences, front-loaded with purpose and examples, followed by a practical usage tip. No wasted words.
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?
Has output schema, so return values are covered. However, given the tool's potential complexity, description could mention result variety or filtering options beyond fail_only.
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?
Schema coverage is 50% (fail_only has a description, patch_id does not). The description does not add meaning beyond the schema; baseline 3 applies with no extra value.
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 clearly states it retrieves CI check results for a patch and lists examples like checkpatch and build_*. However, it does not explicitly differentiate from siblings like get_patch or search_patches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Suggests pairing with get_patch's check_summary for triaging failing series, providing a clear use context. No explicit when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the search and filter functionality but does not disclose behavioral traits like ordering, pagination, read-only nature, or any side effects. The limit parameter suggests pagination but this is not addressed.
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, efficient sentence that front-loads the core action and key filters. No unnecessary words, making it easy to parse quickly.
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?
Given 6 parameters (1 required), no annotations, and an existing output schema, the description is adequate but not thorough. It covers the main filters but omits mention of archived and limit parameters. The output schema mitigates the need to describe returns, but the description could still 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?
Schema description coverage is high (83%), with most parameters having descriptions in the schema. The description adds a summary of key filters (project, state, submitter) but does not provide additional meaning beyond what the schema already conveys. Therefore, it meets the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches patches by name substring with optional filters (project, state, submitter). The verb 'search' and resource 'patches' are specific, and the primary filtering method is mentioned, distinguishing it from sibling tools like get_patch or find_by_msgid.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when searching by name substring with filters, but does not explicitly state when not to use this tool or suggest alternatives (e.g., get_patch for a specific patch, find_by_msgid for message ID). The context signals show siblings but no guidance is provided, so usage is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what data is returned (patch state, delegate, archived flag) but does not explicitly mention side effects, error conditions, or idempotency. Since it is a get operation, the description is adequate but not thorough.
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?
Two sentences, front-loaded with the primary purpose in the first sentence and usage guidance in the second. No unnecessary words, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one parameter and no output schema, the description covers the return data and usage context. Minor gaps exist (e.g., error handling), but overall it provides sufficient context for an AI agent to understand the tool's role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% for the only parameter (series_id), and the description does not explain this parameter at all. The parameter's meaning is entirely left to inference from the parameter name and tool name, which is insufficient for an AI agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Get' and specifies the resource 'series with every patch's state, delegate, and archived flag', clearly stating what the tool returns. It distinguishes itself from siblings by mentioning 'whole patchset', implying it is for retrieving a complete series after finding by message ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to 'Use this after find_by_msgid to see the whole patchset at once,' providing clear context for when to use this tool versus alternatives. This directly references a sibling tool and explains the appropriate workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool looks up across all projects and that results can include multiple projects. It does not cover error behavior, rate limits, or authentication, but for a simple lookup tool the core behavior is adequately described.
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 two sentences long, front-loads the purpose, and contains no filler. Every sentence adds value: the first states the action, the second explains its cross-project nature and use case.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is mostly complete. It explains the cross-project behavior and offers usage guidance. It does not describe the return format, but given its role as a discovery tool, the current description is sufficient.
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 covers the only parameter (msgid) with a description about angle brackets. The tool description does not add new parameter details beyond restating the schema. Since schema coverage is 100%, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Look up patches and cover letters by Message-Id across all projects.' It specifies the resource (patches and cover letters), the key (Message-Id), and the scope (across all projects), which distinguishes it from siblings like get_patch and get_series that likely operate within a single project.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance: 'Use this to discover the projects + series ids before drilling in.' It explains that a single Message-Id can appear under multiple projects, which informs usage. However, it does not explicitly state when not to use this tool or list alternatives, though the sibling names imply other tools for different purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It indicates a read operation with no destructive hints, but does not disclose authentication needs, rate limits, or side effects. For a simple list tool, this is acceptable but minimal.
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?
Two sentences, front-loaded with purpose and output details. No unnecessary words – every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with an output schema present, the description is fully adequate: it states the action and the returned data. There is no missing context for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With no parameters, schema coverage is 100% trivially. Baseline is 4. The description adds value by specifying the output fields, which goes beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and resource 'Patchwork projects', and specifies the returned fields (id, link_name, display name, list_id). It distinguishes from sibling tools which focus on patches, checks, or series.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing available projects, but does not explicitly state when to use versus alternatives or provide exclusions. Since no sibling tool lists projects, the context is clear but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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