better-code-review-graph

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v3.21.0
Disambiguation4/5
Most tools have clearly distinct purposes (config, graph, query, review, security). However, config__open_relay overlaps with config's setup actions, potentially causing confusion about which tool to use for relay configuration.
Naming Consistency3/5
Most tools use single-word names, but config__open_relay introduces a double underscore, breaking the pattern. The naming convention is otherwise consistent with single verbs or nouns.
Tool Count5/5
Seven tools is well-scoped for a code review graph server covering configuration, graph management, querying, review context, and security. Each tool earns its place without overwhelming the agent.
Completeness4/5
The tool surface covers core workflows: config, graph CRUD, querying, review, and security. Minor gaps exist (e.g., no direct delete graph action), but import/export and update cover most needs.
Average 3.6/5 across 7 of 7 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- 89 of 97 community issues answered or closed in the last 6 months
- 224 commits in the last 12 weeks
- Last stable release on July 18, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description describes actions like 'cache_clear (wipe embeddings)' and 'setup_reset (clear credentials)' which imply destructive behavior, but annotations set destructiveHint: false. This is a clear contradiction. Additionally, while it lists some behavioral traits, the inconsistency undermines transparency.
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 a single paragraph that packs many actions into a few lines. While not overly long, it lacks structure (e.g., bullet points) and front-loads the action list without clear organization. It could be more concise by grouping related actions.
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 the tool has 5 parameters, multiple actions, and an output schema, the description is insufficient. It does not describe return values, error conditions, or the output schema, and leaves important details uncovered (e.g., force, repo_root). The agent lacks enough context to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description must compensate but only partially explains parameters. It mentions that for 'set' action, key and value are used and key can be 'log_level', but does not explain force, repo_root, or the required action parameter beyond listing action names. Significant gaps remain.
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 tool's purpose as managing server configuration, status, and credential setup, and lists specific actions (status, set, cache_clear, etc.). It distinguishes from sibling config__open_relay by being the main config tool, but could more explicitly differentiate when to use each.
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 by listing actions and their effects (e.g., 'status (show state)', 'cache_clear (wipe embeddings)'), but does not explicitly state when to use this tool versus alternatives like 'help' or 'config__open_relay'. It only mentions 'Use `help` tool for full docs', which is weak guidance.
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?
Annotations indicate not read-only or destructive, but the description adds little behavioral detail. It implies the tool modifies state (build, update) but doesn't disclose side effects or prerequisites.
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?
Description is dense but somewhat verbose. It lists actions and parameters inline, which is functional but not optimally structured. Could be more front-loaded.
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?
With 9 parameters and only 1 required, and no schema descriptions, the description is insufficient. It covers action-to-parameter mapping but fails to explain parameter semantics and behavior. Output schema existence may help but is not referenced.
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 has 0% coverage, so description must compensate. It connects actions to parameters (e.g., build requires full_rebuild, base, repo_root), adding meaning beyond bare names. However, still omits explanation for several parameters like roots and format.
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?
Description clearly states the tool builds and manages a code knowledge graph, and lists specific actions. This distinguishes it from sibling tools like query or review.
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. The description lists actions but does not provide context for selecting between them or other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description aligns by presenting read-like actions (query, search, impact, diff). The description adds behavioral detail per action (e.g., 'spot_check returns random callsite snippets'), enhancing transparency beyond annotations.
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?
The description is information-dense, packing multiple actions and their arguments into a single paragraph without excessive verbosity. It is not structured with sections but remains focused. The mention of 'help' for full docs prevents over-expansion.
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 21 parameters and high complexity, the description provides a high-level overview of actions but lacks depth on many parameters. An output schema exists, which helps, but the description still leaves gaps regarding parameter usage and edge cases.
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 0%, so the description must explain parameters. It maps some parameters to actions (e.g., pattern, target for query), but many parameters (kind, repo, as_of, limit, languages, etc.) remain unexplained, limiting practical guidance.
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 tool queries a 'code knowledge graph' and lists specific actions like query, search, impact, etc. It distinguishes itself from siblings like config or help by detailing unique functionalities, though it does not explicitly differentiate from the sibling 'graph' tool.
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?
The description lacks guidance on when to use this tool versus alternatives. It lists actions but does not specify when to use a particular action or when not to use the tool. The only direction is 'Use help tool for full docs,' which defers responsibility.
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?
Annotations are sparse (no readOnlyHint, destructiveHint false) and provide little safety context. The description lists actions but does not disclose side effects, authorization needs, or limitations beyond scanning. No contradiction, but insufficient behavioral details.
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-load the tool's purpose, followed by a compact enumeration of actions and parameters. No wasted words; every element adds value.
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?
With 6 parameters and 0% schema coverage, the description covers actions and key constraints but defers to the help tool for full docs. The output schema exists but is not referenced, leaving return values unexplained. Adequate but incomplete.
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?
Schema description coverage is 0%, yet the description adds significant meaning by listing parameter values per action (e.g., engine='heuristic'|'semgrep', format='json'|'sarif'). This compensates for the schema's lack of description.
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: 'Security scanning over the code knowledge graph.' It enumerates four specific actions (scan, report, suppress, rule_list) with their parameters, differentiating it from sibling tools like config, graph, query, and review.
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 explicit guidance on when to use this tool versus alternatives. The mention 'Use `help` tool for full docs' implies incomplete documentation but does not provide context for selection or exclusion.
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 provided, so description must cover behavior. It mentions launching browser and returning status, but does not disclose potential side effects (e.g., browser pop-ups) or whether any state is modified.
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 with no fluff. Every sentence adds value: first states action, second states what is returned.
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 simple parameterless tool, the description fully covers purpose and return values. Output schema exists but description already aligns with it.
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?
No parameters to describe, so baseline 4. The description clarifies that the tool takes no input and performs a specific action, adding context 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?
Clearly states the action (open relay configuration form) and the specific resource (better-code-review-graph). Distinguishes from sibling tools like config or graph by being specific to relay configuration.
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?
No explicit guidance on when to use this tool vs alternatives. The description implies its use for opening the relay form but lacks context about prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing safety. The description adds significant behavioral context: auto-detection of changed files, output structure (structural summary, impacted nodes, source snippets), and conditional behavior for 'show_line_shifts'. No contradictions with annotations.
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?
The description is efficiently structured: starts with the primary purpose, then lists actions and their parameters. It avoids redundancy and front-loads the most important information. A minor density of technical details is acceptable.
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?
Given 12 parameters, 100% schema coverage, and an output schema, the description covers the tool's behavior well. It explains both actions, parameter defaults, and key behaviors. The slight reliance on the 'help' tool for 'full docs' indicates a minor gap, but overall it is sufficiently 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 100%, so the baseline is 3. The description adds value by grouping parameters under each action and providing examples (e.g., 'repo='repo_a-aaaaaaaa''), but it mostly reiterates schema descriptions. The grouping and context slightly elevate it from the baseline.
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 generates 'token-efficient review context for code changes' with two distinct actions: 'context' and 'delta'. It specifies verbs ('generate', 'auto-detects', 'returns') and the resource ('code review context'). While not explicitly distinguishing from siblings, the purpose is specific enough to make the tool's role clear against other tools like 'graph' or 'query'.
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 explicit guidance on when to use each action: 'context' for automatic git diff analysis and 'delta' for comparing two commits. It even details delta's 'show_line_shifts' option for refactor auditing. It lacks explicit 'when not to use' but offers clear context and refers to the 'help' tool for full documentation, which is reasonable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that it returns 'full documentation', which is consistent and implies a safe, read-only operation. No contradictions.
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: first states purpose, second gives usage guideline. No wasted words, front-loaded information.
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 simple doc lookup tool with one optional parameter and an output schema, the description adequately covers purpose, usage, and available topics. Output schema handles return value documentation.
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?
Schema has one parameter 'topic' with no enum, but description lists specific topics (graph, query, review, etc.), adding meaning beyond schema. Schema coverage is 0%, so description compensates well.
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?
Description clearly states verb 'Get full documentation' and resource 'any tool'. Lists specific topics (graph, query, etc.), which distinguishes it from sibling tools that are the tools themselves.
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 says 'Use when compressed descriptions are insufficient', providing clear guidance on when to invoke this tool. Also lists available topics for reference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![better-code-review-graph MCP server](https://glama.ai/mcp/servers/n24q02m/better-code-review-graph/badges/card.svg)](https://glama.ai/mcp/servers/n24q02m/better-code-review-graph)

Score Badge

Copy to your README.md:

[![better-code-review-graph MCP server](https://glama.ai/mcp/servers/n24q02m/better-code-review-graph/badges/score.svg)](https://glama.ai/mcp/servers/n24q02m/better-code-review-graph)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/n24q02m/better-code-review-graph'

If you have feedback or need assistance with the MCP directory API, please join our Discord server