MCP Maker

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes focused on different aspects of MCP development (templates, documentation, project setup), though 'generate_doc_enriched_template' and 'generate_mcp_boilerplate' could potentially overlap in creating server templates. The descriptions help clarify that one is documentation-enhanced while the other is general boilerplate.
Naming Consistency4/5
Tools follow a consistent verb_noun pattern with clear actions like 'create', 'generate', 'get', 'save', and 'search'. There's minor deviation with 'generate_doc_enriched_template' using a compound adjective, but overall naming is predictable and readable.
Tool Count5/5
With 8 tools, this is well-scoped for an MCP development assistant. Each tool serves a specific purpose in the workflow (template creation, documentation handling, project setup), and none feel redundant or unnecessary for the server's apparent domain.
Completeness4/5
The toolset covers key MCP development needs: creating templates for prompts, resources, and tools; accessing and searching documentation; and generating server boilerplate. A minor gap might be the lack of tools for testing or deploying MCP servers, but core development workflows are well-supported.
Average 2.8/5 across 8 of 8 tools scored.
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
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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

Behavior2/5
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 the tool creates files, implying a write operation, but lacks details on permissions, side effects, error handling, or output format. This is inadequate for a tool that likely modifies the filesystem.
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 a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded and appropriately sized, though it could benefit from additional context to improve usability.
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's complexity (5 parameters, no annotations, no output schema), the description is incomplete. It lacks parameter explanations, behavioral details, and output information, making it insufficient for an agent to reliably use the tool without guesswork.
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?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The tool description does not mention any parameters, failing to compensate for this gap. Parameters like 'project_name', 'description', 'output_dir', 'include_prompts', and 'include_resources' are left unexplained, hindering effective tool invocation.
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: 'Creates a new MCP server project with all the necessary boilerplate files.' It specifies the verb ('Creates') and resource ('MCP server project'), though it doesn't explicitly differentiate from sibling tools like 'generate_doc_enriched_template' or 'create_tool_template' which might have overlapping purposes.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for project creation, or compare it to sibling tools such as 'create_tool_template' or 'generate_doc_enriched_template', leaving the agent to infer usage scenarios.
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?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Generates' implies a write operation that creates files, it doesn't disclose important behavioral aspects: whether it overwrites existing files, what permissions are needed, what format the output takes, or whether it's idempotent. The description provides minimal behavioral context beyond the basic action.
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 extremely concise - a single sentence that gets straight to the point with zero wasted words. It's front-loaded with the core action and doesn't include any unnecessary elaboration. For a tool that generates code templates, this level of brevity is appropriate if supplemented by good parameter documentation.
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?
For a tool with 4 required parameters, 0% schema description coverage, no annotations, and no output schema, the description is severely inadequate. It doesn't explain what the tool actually produces, what the parameters mean, or how the generated template should be used. The description leaves too many unanswered questions for effective tool invocation.
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 0% schema description coverage for all 4 required parameters, the description provides absolutely no information about what each parameter means or how they should be used. The description doesn't mention any of the parameters (resource_name, resource_uri_pattern, description, output_dir), leaving the agent with no semantic understanding of what values to provide.
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 with a specific verb ('Generates') and resource ('template code for a new MCP resource'). It distinguishes from siblings like 'create_prompt_template' and 'create_tool_template' by specifying it's for resources, not prompts or tools. However, it doesn't fully differentiate from 'generate_mcp_boilerplate' which might serve a similar purpose.
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 provides no guidance on when to use this tool versus alternatives. With siblings like 'create_prompt_template', 'create_tool_template', and 'generate_mcp_boilerplate' that likely serve related template generation purposes, there's no indication of when this specific resource template tool is appropriate versus those other options.
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 the full burden of behavioral disclosure. While 'Generates template code' implies a creation/write operation, the description doesn't specify what happens to existing files, whether it overwrites or creates new files, what permissions are needed, or what the output looks like. For a tool that creates files with 4 required parameters, this is insufficient 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point. It's appropriately sized for the tool's complexity, with no wasted words or unnecessary elaboration. The structure is front-loaded with the core functionality immediately clear.
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?
For a tool with 4 required parameters, 0% schema description coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain what the generated template includes, what format it produces, how parameters affect the output, or what happens in the output_dir. The description leaves too many open questions about the tool's behavior and output.
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?
Schema description coverage is 0%, meaning none of the 4 parameters have descriptions in the schema. The description mentions 'customizable parameters' but doesn't explain what those parameters are or their purposes. It doesn't compensate for the complete lack of parameter documentation in the schema, leaving all 4 required parameters (tool_name, description, parameters, output_dir) semantically undefined.
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: 'Generates template code for a new MCP tool with customizable parameters'. It specifies the verb ('Generates'), resource ('template code'), and scope ('new MCP tool'), but doesn't explicitly differentiate it from sibling tools like 'create_prompt_template' or 'generate_mcp_boilerplate' which might have overlapping functionality.
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 provides no guidance on when to use this tool versus alternatives. With siblings like 'create_prompt_template', 'create_resource_template', and 'generate_mcp_boilerplate', there's no indication of which tool to choose for different template generation scenarios. The description only states what it does, not when it's 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?
With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions generating a template with documentation context but doesn't disclose what the template includes, how it's structured, whether it overwrites files, or any permissions/rate limits. This is inadequate for a tool with 4 parameters and no 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.
Conciseness5/5
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, directly stating the tool's purpose without unnecessary elaboration.
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 with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain what the generated template contains, how parameters interact, or what the output looks like, leaving too many gaps for effective use.
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?
Schema description coverage is 0%, so the description must compensate but adds no parameter details. It doesn't explain what 'doc_context', 'output_dir', etc., mean or how they're used. With 4 undocumented parameters, this is a significant gap, scoring below the baseline of 3.
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 action ('Generate') and resource ('MCP server template'), specifying it uses 'context from the documentation'. It distinguishes from siblings like 'generate_mcp_boilerplate' by mentioning documentation context, but doesn't explicitly contrast with all siblings like 'create_tool_template'.
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 is provided. The description implies usage when documentation context is needed, but doesn't specify scenarios, prerequisites, or exclusions compared to sibling tools like 'create_resource_template' or 'generate_mcp_boilerplate'.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'Get[s] a specific section', implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns errors for missing keys, or details the output format. This leaves significant gaps for a tool with two parameters.
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 parameters without any wasted words. It's appropriately sized for the tool's complexity, making it easy to parse quickly.
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 complexity (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't cover behavioral aspects like error handling or output structure, and with low schema coverage, it fails to fully explain parameter meanings. This leaves the agent with insufficient context for reliable use.
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?
The schema description coverage is 0%, so the description must compensate. It mentions 'key and section title', which maps to the two parameters, but doesn't explain what a 'key' represents (e.g., document ID, path) or what 'section_title' entails (e.g., exact match, case sensitivity). This adds minimal value beyond naming the parameters.
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 'specific section of MCP documentation', making the purpose understandable. It distinguishes from siblings like 'search_mcp_docs' by focusing on retrieval by key and title rather than searching. However, it doesn't explicitly differentiate from 'save_mcp_docs' or other siblings, keeping it from a perfect score.
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 provides no guidance on when to use this tool versus alternatives like 'search_mcp_docs' or 'save_mcp_docs'. It lacks context on prerequisites, such as needing existing documentation keys, and doesn't mention any exclusions or best practices for usage.
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 the full burden of behavioral disclosure. It states the tool generates code, implying a write operation, but doesn't cover critical aspects like file system effects (e.g., whether it overwrites existing files), permissions needed, error handling, or output format. This is a significant gap for a tool that likely creates files.
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 directly states the tool's function without any fluff. It's appropriately sized and front-loaded, making it easy to grasp immediately.
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 complexity of a code-generation tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavior, parameter meanings, and expected outcomes, which are essential for effective use. The conciseness comes at the cost of necessary context.
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 schema description coverage is 0%, so the description must compensate, but it adds no parameter information beyond what's inferred from the tool name. It doesn't explain the meaning of parameters like 'include_variables' or 'output_dir', leaving them undocumented. However, the tool name and description imply parameters related to prompt creation, providing minimal context.
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 action ('Generates') and the resource ('template code for a new MCP prompt'), making the purpose understandable. However, it doesn't differentiate this tool from its siblings like 'create_resource_template' or 'create_tool_template', which likely generate similar templates for different MCP components.
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 provides no guidance on when to use this tool versus alternatives such as 'create_resource_template' or 'generate_mcp_boilerplate'. There's no mention of prerequisites, typical scenarios, or exclusions, leaving usage context entirely implicit.
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?
With no annotations provided, the description carries full burden but only states it 'saves' and 'stores' without detailing permissions, persistence mechanisms, error handling, or response format. It lacks critical behavioral context for a write operation.
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 with no wasted words, clearly front-loaded with the core action. Every word contributes to the tool's purpose.
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?
For a write tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't address how storage works, what 'key' represents, or what happens on success/failure, leaving significant gaps for agent usage.
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 compensate but only implies parameters through 'MCP documentation text' and 'stores it', without explaining 'key' or 'doc_text' meanings. It adds minimal value beyond the schema's property names.
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 action ('saves') and resource ('MCP documentation text'), specifying it stores for future reference. However, it doesn't differentiate from siblings like 'create_resource_template' or 'generate_mcp_boilerplate' which might also involve saving documentation-related content.
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 'create_resource_template' or 'search_mcp_docs'. The description implies storage for reference but doesn't specify use cases, prerequisites, or exclusions.
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?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'search' but doesn't describe how results are returned (e.g., format, ranking, pagination), what constitutes 'relevant information', or any limitations (e.g., search scope, performance). This leaves significant gaps for an agent to understand the tool's behavior.
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 with no wasted words. It's appropriately sized for a simple search tool and front-loads the core purpose without unnecessary elaboration.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the search returns (e.g., documents, snippets, metadata), how results are structured, or any behavioral nuances. For a search tool with no structured context, this leaves the agent with insufficient information to use it effectively.
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 schema has 0% description coverage, so the description must compensate. It implies a 'query' parameter is needed for searching but doesn't explain what the query should contain (e.g., keywords, natural language) or any constraints beyond the schema's 'minLength: 1'. This adds minimal semantic value beyond what the schema structure indicates.
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 action ('Search through') and resource ('stored MCP documentation'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_mcp_doc_section', which might retrieve specific sections rather than search across all documentation.
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 provides no guidance on when to use this tool versus alternatives like 'get_mcp_doc_section' or 'save_mcp_docs'. It lacks context about appropriate scenarios, exclusions, or comparisons with sibling tools.
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:

[![mcp-maker MCP server](https://glama.ai/mcp/servers/CaptainCrouton89/mcp-maker/badges/card.svg)](https://glama.ai/mcp/servers/CaptainCrouton89/mcp-maker)

Score Badge

Copy to your README.md:

[![mcp-maker MCP server](https://glama.ai/mcp/servers/CaptainCrouton89/mcp-maker/badges/score.svg)](https://glama.ai/mcp/servers/CaptainCrouton89/mcp-maker)

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/CaptainCrouton89/mcp-maker'

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