mcp-server-collector
The mcp-server-collector server is designed to collect and manage MCP Servers. It can:
Extract MCP Servers from a specified URL
Extract MCP Servers from provided text content
Submit discovered MCP Servers to directories like mcp.so, with an optional avatar URL
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., "@mcp-server-collectorextract MCP servers from https://github.com/modelcontextprotocol/servers"
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.
mcp-server-collector MCP server
A MCP Server used to collect MCP Servers over the internet.
Components
Resources
No resources yet.
Prompts
No prompts yet.
Tools
The server implements 3 tools:
extract-mcp-servers-from-url: Extracts MCP Servers from given URL.
Takes "url" as required string argument
extract-mcp-servers-from-content: Extracts MCP Servers from given content.
Takes "content" as required string argument
submit-mcp-server: Submits a MCP Server to the MCP Server Directory like mcp.so.
Takes "url" as required string argument and "avatar_url" as optional string argument
Related MCP server: MCP Server Neurolorap
Configuration
.env file is required to be set up.
OPENAI_API_KEY="sk-xxx"
OPENAI_BASE_URL="https://api.openai.com/v1"
OPENAI_MODEL="gpt-4o-mini"
MCP_SERVER_SUBMIT_URL="https://mcp.so/api/submit-project"Quickstart
Install
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development
Building and Publishing
To prepare the package for distribution:
Sync dependencies and update lockfile:
uv syncBuild package distributions:
uv buildThis will create source and wheel distributions in the dist/ directory.
Publish to PyPI:
uv publishNote: You'll need to set PyPI credentials via environment variables or command flags:
Token:
--tokenorUV_PUBLISH_TOKENOr username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
npx @modelcontextprotocol/inspector uv --directory path-to/mcp-server-collector run mcp-server-collectorUpon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
Community
About the author
Available Tools
3 toolsextract-mcp-servers-from-contentC
Extract MCP Servers from given content
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | content containing mcp servers |
TDQS
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 only states what the tool does ('extract MCP servers') without explaining how it behaves: e.g., what format the extraction outputs, whether it's read-only or has side effects, error handling, or performance considerations. This is inadequate for a tool with no annotation coverage, as it leaves critical behavioral traits unspecified.
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 extremely concise with a single sentence: 'Extract MCP Servers from given content'. It is front-loaded and wastes no words, making it easy to parse. Every part of the sentence earns its place by stating the action and target, though it could benefit from more detail for clarity.
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 extraction tasks, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'extract' entails (e.g., parsing, formatting, or validation), what the output looks like, or how it differs from sibling tools. For a tool with no structured support beyond the input schema, this leaves significant gaps in understanding its full context and usage.
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 description adds no meaning beyond what the input schema provides. The schema has 100% coverage with one parameter 'content' described as 'content containing mcp servers', which the description implicitly references but doesn't elaborate on. With high schema coverage, the baseline is 3, as the schema already documents the parameter adequately, and the description doesn't compensate with additional context like examples or constraints.
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 states the tool's purpose as extracting MCP servers from content, which is clear but vague. It specifies the verb 'extract' and resource 'MCP servers', but doesn't differentiate from sibling tools like 'extract-mcp-servers-from-url' or 'submit-mcp-server' beyond the input source. The purpose is understandable but lacks specificity about what constitutes 'extraction' versus 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. It doesn't mention when to prefer this tool over 'extract-mcp-servers-from-url' (e.g., for direct content vs. URL fetching) or 'submit-mcp-server' (e.g., for extraction vs. submission). There's no context on prerequisites, exclusions, or typical use cases, 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.
extract-mcp-servers-from-urlC
Extract MCP Servers from a URL
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states what the tool does but lacks behavioral details: no information on permissions needed, rate limits, error handling, output format, or whether it's read-only/destructive. 'Extract' suggests read-only, but this isn't explicitly confirmed.
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 for a simple tool and front-loaded with the core action, making it easy to parse quickly.
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 no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameters, and return values, which are essential for a tool with one parameter and potential complexity in URL processing and MCP server extraction.
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 0% with 1 parameter ('url'), and the description doesn't add any parameter semantics beyond the name. It doesn't explain what type of URL is expected (e.g., HTTP, file path), format constraints, or examples, leaving the parameter meaning unclear.
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 'Extract MCP Servers from a URL' clearly states the verb ('extract'), resource ('MCP Servers'), and source ('from a URL'). It distinguishes from sibling 'extract-mcp-servers-from-content' by specifying URL vs. content, but doesn't differentiate from 'submit-mcp-server' which has a different action.
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 explicit guidance on when to use this tool vs. alternatives. The description implies usage for URL-based extraction, but doesn't specify scenarios, prerequisites, or exclusions compared to siblings like 'submit-mcp-server' for submission operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit-mcp-serverC
Submit MCP Server to MCP Servers Directory like mcp.so
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the MCP Server to submit | |
| avatar_url | No | avatar URL of the MCP Server to submit |
TDQS
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 submits to a directory 'like mcp.so', implying a public listing or registration, but doesn't clarify permissions required, rate limits, whether the submission is reversible, or what happens on success/failure. This is inadequate for a tool that likely involves external API calls.
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 directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral details like authentication needs. For a submission tool with external dependencies, this leaves significant gaps in understanding how to use it effectively.
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 both parameters ('url' and 'avatar_url') with clear descriptions. The description adds no additional meaning about parameters beyond what the schema provides, such as format examples or constraints, meeting 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 action ('Submit') and resource ('MCP Server to MCP Servers Directory like mcp.so'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'extract-mcp-servers-from-content' or 'extract-mcp-servers-from-url', which appear to be extraction tools rather than submission tools.
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. It doesn't mention prerequisites, context for submission, or how it differs from sibling tools, leaving the agent to infer usage 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.
TDQS
Each tool has a clearly distinct purpose with no overlap: extracting servers from content, extracting from a URL, and submitting to a directory. The descriptions make it unambiguous which tool to use for each scenario, preventing misselection.
All tool names follow a consistent verb_noun pattern with hyphens (e.g., extract-mcp-servers-from-content, extract-mcp-servers-from-url, submit-mcp-server). This predictable naming scheme enhances readability and usability for agents.
With 3 tools, the server is well-scoped for its purpose of collecting and submitting MCP servers. Each tool earns its place by covering distinct aspects of the workflow, avoiding bloat or thinness.
The tool set covers the core workflow of extraction (from content and URLs) and submission, with no obvious dead ends. A minor gap might be the lack of tools for managing or listing already submitted servers, but agents can work around this with the existing tools.
Maintenance
Resources
Unclaimed servers have limited discoverability.
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