repo-context-mcp
Server Quality Checklist
Latest release: v0.1.1
- Disambiguation5/5
Each tool performs a unique, non-overlapping function: repo_map provides structural overview, search_code locates specific lines, and pack_context bundles relevant files for LLM consumption. There is no ambiguity about when to use which tool.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern (repo_map, search_code, pack_context) using lowercase with underscores. The naming is uniform and predictable.
Tool Count5/5With exactly 3 tools, the server is well-scoped for its purpose—providing repo context. Each tool earns its place without redundancy, and the count is neither too sparse nor overwhelming.
Completeness5/5The tool set covers the complete workflow of understanding a repository: mapping the structure, searching for specific content, and packing the most relevant files into a context bundle. There are no obvious gaps for the stated purpose.
Average 4.2/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- Last stable release on
- 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
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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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses meaningful behavioral details: token budgeting, relevance ranking, and the heuristic 'Prefer entrypoints and paths matching focus keywords'. However, it does not describe output structure or potential side effects, which keeps it from a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loaded with the core purpose and followed by usage guidance. Every word contributes value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a relatively simple tool with a fully described 4-parameter schema and no output schema, the description covers purpose, usage, and selection behavior. It could mention the exact structure of the markdown bundle, but it is largely complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage of all four parameters with clear descriptions. The tool description adds little beyond the schema, only reinforcing the role of 'focus' keywords. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'packs a token-budgeted markdown bundle of the most relevant source files for an LLM', with a specific verb and resource. It also distinguishes from siblings by implying this assembles context rather than just mapping or searching code.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases: 'Use for PR review or task kickoff.' This gives clear context for when to use the tool, but it does not explicitly name alternatives or when-not-to-use conditions, so it falls short of a 5.
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?
With no annotations, the description carries the burden for behavioral disclosure. It adds a key behavioral fact: 'Honors .gitignore.' It also implies read-only behavior via 'lightweight map' and orientation. However, it does not elaborate on edge cases (e.g., symlinks, file content exclusion), but for a mapping tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is just two sentences: the first defines the tool's core function and outputs, the second provides usage guidance and a key behavior. Every sentence earns its place with no waste, and the most critical information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool with no output schema, the description covers the main aspects: what it produces, when to use it, and a notable behavior. It does not detail return format, but that is partially inferred from the listed outputs. Sibling differentiation could be stronger, but overall it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all three parameters (root, max_depth, max_entries) explained in the schema. The description adds no additional parameter semantics beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Build a lightweight repository map: directory tree, file count, and likely entrypoints/manifests.' It specifies the verb (build), resource (repository map), and concrete outputs. This differentiates it from sibling tools like search_code (searching) and pack_context (packing) by framing it as an orientation tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this first to orient before reading files,' providing clear guidance on when to use the tool. It implies an ordering relative to sibling tools but does not explicitly name alternatives or exclusions, so it falls short of a flawless 5.
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?
With no annotations, the description carries the full burden. It discloses key behaviors: case-insensitive default, return format (path:line hits with surrounding line text), and the skipping of .gitignore and vendor dirs. This goes beyond basic operation and addresses important edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, each earning its place: action, return format, and skip behavior. Front-loaded with the primary purpose, no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description properly explains the return format. It covers default behavior and project-ignoring rules. It does not mention max_results default, but the schema covers that, so completeness is high for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 minimal extra meaning beyond the schema: it restates case-insensitivity (already in schema) and mentions output format, but does not elaborate on parameter semantics beyond what properties already describe.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches source files for a substring, with a specific verb ('Search') and resource ('source files'). It also distinguishes itself from siblings (repo_map, pack_context) by its unique focus on substring search with output details (path:line hits).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on what the tool does, making it obvious when to use it (e.g., finding string occurrences in code). It does not explicitly mention alternatives, but the siblings are for mapping/packing context, so the usage is clear. It lacks explicit exclusions, but the context is sufficient.
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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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.
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