gread
Server Details
An MCP server that gives your AI access to the source code and docs of all public github repos
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- NitroRCr/gread
- GitHub Stars
- 57
- Server Listing
- Gread
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.4/5 across 5 of 5 tools scored.
Each tool has a clear, distinct purpose: listing directory trees, reading source code, searching code, searching repositories, and viewing repository info. No overlaps.
All tool names follow a consistent verb_noun pattern (list_tree, read_code, search_code, search_repos, view_repo), making them predictable.
With 5 tools, the server is appropriately scoped for code reading and searching tasks, neither too sparse nor overloaded.
Covers key read operations like directory listing, code retrieval, code search, repo search, and repo info. Minor gaps: no file metadata or commit history, but core functionality is solid.
Available Tools
5 toolslist_treeBInspect
List the directory tree of a specific path in a repository with customizable depth and traversal limits.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Full name of the repository (owner/name) | |
| maxDepth | No | Maximum depth into the directory structure to list. | |
| maxPerDir | No | Maximum number of items to display per directory level. | |
| targetDir | No | Target directory path to inspect. Leaves empty to search from root. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions customizable depth and traversal limits, giving some behavioral context. However, it does not specify whether the listing includes files, only directories, or the structure of the output, which is important for a tool without an output schema.
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 a single sentence of 17 words, very concise and front-loaded. It efficiently conveys the core purpose but could benefit from a second sentence to add usage or behavioral details without harming conciseness.
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 four parameters, no output schema, and no annotations, the description is insufficiently complete. It fails to explain what the tool returns (e.g., does it show files? truncated output?), which is critical for an agent to anticipate the tool's behavior.
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 schema has 100% description coverage for parameters, so the description adds no new meaning beyond restating that depth and traversal limits are customizable. It does not provide additional context or examples that would enhance understanding.
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 lists the directory tree of a specific path in a repository, with customizable depth and traversal limits. It distinguishes itself from sibling tools like read_code and search_code by focusing on directory structure listing.
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 provides no guidance on when to use this tool versus alternatives or any exclusions. It does not mention scenarios where this tool is appropriate or not, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_codeAInspect
Retrieve the raw source code of specified files from within a known repository.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Full name of the repository (owner/name) | |
| paths | Yes | An array of precise file paths within the repository |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description carries full burden. It implicitly suggests a read operation but does not explicitly state it is read-only, nor mention permissions, rate limits, or error handling. Adequate 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. Every word contributes to the purpose.
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?
For a simple 2-parameter tool with no output schema, the description is adequate but lacks details on file-not-found behavior, encoding, or size limits. Slightly incomplete.
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 100% with descriptions for both parameters. The description adds no additional meaning beyond the schema, so baseline 3 applies.
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?
Description clearly states the action (retrieve), resource (raw source code), and context (known repository). It distinguishes from sibling tools like search_code which searches code, and list_tree which lists directory structure.
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?
No guidance on when to use this tool versus alternatives like search_code or list_tree. The description does not mention when not to use it or provide context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_codeAInspect
Perform a fast git grep inside the repository, allowing regex matching by default or substring search.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Full name of the repository (owner/name) | |
| path | No | Directory or file path to limit the search scope | |
| query | Yes | Search pattern or query to pass to git grep | |
| ignoreCase | No | Ignore case distinctions in both the PATTERN and the input files (-i) | |
| contextLines | No | Print num lines of output context (-C) | |
| fixedStrings | No | Use fixed strings for patterns (don’t interpret pattern as a regex) (-F) | |
| extendedRegexp | No | Use extended regular expressions (-E) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that regex is the default matching mode and that substring search is possible, but does not mention other behavioral traits like read-only nature, authorization needs, rate limits, or result format.
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?
Single sentence with front-loaded purpose, no wasted words. Efficiently conveys core functionality.
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?
Description covers basic purpose but lacks details on output format, error conditions, or parameter usage nuances. With no output schema, completeness is moderate.
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 100%, so baseline is 3. The description adds value by explaining default regex behavior (not in schema) and performance ('fast'), exceeding baseline.
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 performs a fast git grep inside the repository, specifying the verb (perform), resource (git grep inside repository), and capabilities (regex by default or substring). It is distinct from siblings like list_tree, read_code, search_repos, and view_repo, which focus on other operations.
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 provides no guidance on when to use this tool versus alternatives, such as search_repos (which might search repository names). It does not mention exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_reposAInspect
Search for GitHub repositories by name, description, or topic keywords using the GitHub Search API.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Keyword to search in repository names, descriptions, or topics |
Tool Definition Quality
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 mentions using the GitHub Search API but fails to disclose key behavioral traits such as rate limits, pagination, result limits, or whether results are sorted, which are critical for agent invocation.
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 a single, front-loaded sentence with no wasted words. Every element serves a purpose.
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 has one parameter and no output schema, the description is adequate but leaves gaps about response format, pagination, and result sorting. It does not fully prepare an agent for invocation.
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 100% (one parameter documented in schema). The description adds no extra meaning beyond the schema's parameter description, meeting the baseline of 3 but not exceeding it.
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 verb 'Search' and the resource 'GitHub repositories'. It specifies searchable fields (name, description, topics) and the underlying API, distinguishing it from sibling tools like search_code or view_repo.
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 implies usage for searching repositories by name, description, or topics, but provides no explicit guidance on when to use this tool versus alternatives like search_code, nor does it mention any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
view_repoBInspect
View repository basic information and its directory structure. Includes corresponding documentation repo if available.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Full name of the repository (owner/name) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions inclusion of documentation repo but lacks details on read-only nature, permissions, error handling, or side effects. More transparency needed.
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?
Two concise sentences that efficiently convey purpose and a key behavioral trait. No unnecessary words.
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?
Adequate for a simple tool with one parameter and no output schema, but could be more specific about what 'basic information' includes and what the directory structure output looks like.
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 100%, so baseline 3. Tool description does not add any additional meaning beyond 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?
Description clearly states verb 'View' and resources 'repository basic information' and 'directory structure', and distinguishes from siblings by mentioning documentation repo inclusion.
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?
No guidance on when to use this tool versus alternatives like list_tree or search_repos. The description does not provide any usage context or exclusions.
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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{
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"maintainers": [{ "email": "your-email@example.com" }]
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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