Enables interaction with the GitHub API, providing tools for creating issues, retrieving repository information, listing repository issues, and searching repositories.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@GitHub MCP Server create an issue in my todo-app repo about fixing the login bug"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Hello! This is a GitHub MCP server designed to enable MCP-compatible LLMs, such as Claude, to communicate with my MCP server and interact with the GitHub API.
TypeScript (programming language)
Octokit (for making API requests to GitHub)
Model Context Protocol SDK
Clone the repository
Run npm install
Add .env file looking at the sample provided in .env.example file
To build the TypeScript files to Javascript, run npx tsc
To finally run the project, run node build/index.js
Related MCP server: mcp-server-github
You can test your MCP server in 2 ways:
MCP inspector
Claude Desktop
Simply run npx @modelcontextprotocol/inspector node build/index.js in the terminal
Go to http://localhost:5173
You can now see the MCP inspector and test.
Download and install Claude Desktop from here
Go to File > Settings... > Developer > Edit Config
It should open up the location of claude_desktop_config.json file.
Open that file in your code editor and add the following:
{
"mcpServers": {
"gh": {
"command": "node",
"args": ["absolute\\path\\to\\your\\index.js\\file"],
"env": {
"GITHUB_TOKEN": "your-github-personal-access-token"
}
}
}
}Exit and reopen Claude desktop
The MCP supports mainly two features:
Tools (4)
create-issue: create a new issue in a GitHub repository
get-repo-info: get information about a specific GitHub repository
list-issues: list issues in a GitHub repository
search-repos: Search for GitHub repositories
Prompts (5)
create-issue-description: generate a description for a GitHub issue
create-pull-request-description: generate a description for a GitHub pull request
search-repos-prompt: generate a query for searching GitHub repositories
create-issue-prompt: generate parameters for creating a GitHub issue
enhance-github-response: format and enhance raw GitHub API response data
You can write your own prompts or select a suitable prompt from the dropdown in the "Choose an integration" option for MCP in Claude desktop
Create a new issue in a GitHub repository
| Name | Required | Description | Default |
|---|---|---|---|
| owner | Yes | Repository owner (username or organization) | |
| repo | Yes | Repository name | |
| title | Yes | Issue title | |
| body | Yes | Issue body | |
| labels | No | Labels to apply to the issue |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Create' implies a write/mutation operation, the description doesn't disclose important behavioral traits like authentication requirements, rate limits, whether the operation is idempotent, what happens on duplicate titles, or what the response looks like. It's minimal for a mutation tool.
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, efficient sentence that states the core purpose without any wasted words. It's appropriately sized and front-loaded with the essential information.
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 mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't address authentication needs, error conditions, response format, or behavioral constraints. While the schema covers parameters well, the overall context for using this tool is 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?
With 100% schema description coverage, all 5 parameters are already documented in the input schema. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters, provide examples, or clarify edge cases. The baseline of 3 is appropriate when the schema does the heavy lifting.
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 action ('Create a new issue') and target resource ('in a GitHub repository'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its siblings (get-repo-info, list-issues, search-repos) beyond the obvious difference in operation 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 provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (like authentication needs), when-not-to-use scenarios, or how this differs from related operations in sibling tools beyond the basic function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get information about a specific GitHub repository
| Name | Required | Description | Default |
|---|---|---|---|
| owner | Yes | Repository owner (username or organization) | |
| repo | Yes | Repository name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It doesn't specify whether this is a read-only operation, what permissions might be required, rate limits, error conditions, or what format the returned information takes. The description is too vague to provide adequate behavioral context.
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, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information without unnecessary elaboration.
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 tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what type of repository information is returned, how to interpret results, or any behavioral aspects. Given the lack of structured data, the description should provide more context about the tool's operation and outputs.
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 input schema has 100% description coverage, with both parameters ('owner' and 'repo') clearly documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema, so it meets the baseline score of 3 for high schema coverage.
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 ('Get information') and resource ('about a specific GitHub repository'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search-repos' or 'list-issues', which would require more specificity about what type of repository information is retrieved.
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 like 'search-repos' or 'list-issues'. It doesn't mention prerequisites, context for usage, or any exclusions. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List issues in a GitHub repository
| Name | Required | Description | Default |
|---|---|---|---|
| owner | Yes | Repository owner (username or organization) | |
| repo | Yes | Repository name | |
| state | No | Issue state | |
| limit | No | Maximum number of issues to return |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'List issues' but doesn't describe whether this is a read-only operation, if it requires authentication, how results are paginated or sorted, or what the return format looks like. This leaves significant gaps for a tool that interacts with an external API.
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, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately clear what the tool does without unnecessary elaboration.
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 complexity of interacting with GitHub's API, the lack of annotations, and no output schema, the description is insufficient. It doesn't cover authentication needs, rate limits, error handling, or response structure, leaving critical contextual gaps for effective tool use.
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 description coverage is 100%, with all parameters well-documented in the input schema. The description adds no additional parameter information beyond implying the tool operates on a GitHub repository, which is already covered by the 'owner' and 'repo' parameters. This meets the baseline for high schema coverage.
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 ('List') and resource ('issues in a GitHub repository'), making the tool's purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'search-repos' or 'create-issue', but the core functionality is unambiguous.
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 like 'search-repos' or 'create-issue'. It doesn't mention prerequisites, context for filtering, or any exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for GitHub repositories
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query | |
| sort | No | Sort order | |
| limit | No | Maximum number of results to return |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Search for GitHub repositories' implies a read-only operation but doesn't specify whether it requires authentication, rate limits, pagination behavior, or what the return format looks like. For a search tool with zero annotation coverage, this is a significant gap in transparency.
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, efficient sentence with zero waste. It's appropriately sized and front-loaded, immediately conveying the core functionality without unnecessary elaboration.
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 (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks behavioral details and usage context. Without annotations or output schema, the agent must rely heavily on the input schema and external knowledge.
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 the schema already documents all three parameters (query, sort, limit) with descriptions and enum values. The description doesn't add any meaning beyond what the schema provides, such as query syntax examples or limit defaults. Baseline 3 is appropriate when the schema does the heavy lifting.
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 'Search for GitHub repositories' clearly states the verb ('Search') and resource ('GitHub repositories'), making the tool's purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'get-repo-info' or 'list-issues', but it's unambiguous about what it does.
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 like 'get-repo-info' or 'list-issues'. It doesn't mention any prerequisites, exclusions, or specific contexts for usage, leaving the agent to infer based on tool names alone.
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.
create-issueget-repo-infolist-issuessearch-reposEach tool has a clearly distinct purpose: create-issue handles issue creation, get-repo-info retrieves repository details, list-issues lists existing issues, and search-repos searches for repositories. There is no overlap or ambiguity in functionality.
The naming follows a consistent verb-noun pattern (create-issue, get-repo-info, list-issues, search-repos), with all tools using hyphen-separated lowercase. The minor deviation is that 'get-repo-info' includes an extra 'info' suffix, but overall the pattern is predictable and readable.
With only 4 tools, the set feels thin for a GitHub server, lacking common operations like updating/deleting issues, managing pull requests, or accessing repository contents. While the tools are well-scoped, the count is borderline low for the domain's typical scope.
The tool surface has significant gaps for a GitHub server. It covers basic issue and repository operations but misses critical CRUD/lifecycle coverage (e.g., no update/delete for issues, no pull request tools, no repository modification). This will likely cause agent failures in common workflows.
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