by hqn21
Protocols.io server lets you manage scientific protocols with CRUD features, simplifying tasks with simple network manag
Integrates with protocols.io to search, retrieve, and manage scientific laboratory protocols. Supports full CRUD operations for protocols and their step-by-step procedures.
Protocols.io is a community-built MCP server published by hqn21 that provides AI assistants with tools and capabilities via the Model Context Protocol. Protocols.io server lets you manage scientific protocols with CRUD features, simplifying tasks with simple network manag It is categorized under productivity.
You can install Protocols.io in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Protocols.io is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We evaluated Protocols.io against two servers with overlapping tools; this profile had the clearer scope statement.
Protocols.io is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated Protocols.io against two servers with overlapping tools; this profile had the clearer scope statement.
Protocols.io has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Protocols.io reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend Protocols.io for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Protocols.io has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Protocols.io benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Protocols.io has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We evaluated Protocols.io against two servers with overlapping tools; this profile had the clearer scope statement.
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A Model Context Protocol (MCP) server that enables MCP clients like Claude Desktop to interact with protocols.io, a popular platform for sharing scientific protocols and methods.
The server provides the following tools that can be used by MCP clients:
search_public_protocols - Search for public protocols by keywordget_protocol - Get basic protocol information by IDget_protocol_steps - Get detailed steps for a specific protocolget_my_protocols - Retrieve all protocols from your accountcreate_protocol - Create a new protocol with title and descriptionupdate_protocol_title - Update the title of an existing protocolupdate_protocol_description - Update the description of an existing protocolset_protocol_steps - Replace all steps in a protocoladd_protocol_step - Add a single step to the end of a protocoldelete_protocol_step - Delete a specific step from a protocol{your_mcp_base_url}/auth/callbackdocker run -d -p 8000:8000 -e PROTOCOLS_IO_CLIENT_ID="your_client_id" -e PROTOCOLS_IO_CLIENT_SECRET="your_client_secret" -e PROTOCOLS_IO_MCP_BASE_URL="https://example.com" --name protocols-io-mcp --restart always ghcr.io/hqn21/protocols-io-mcp:latest
The server will be accessible at http://0.0.0.0:8000/mcp with HTTP transport
pip install protocols-io-mcp
export PROTOCOLS_IO_CLIENT_ACCESS_TOKEN="your_client_access_token"
export PROTOCOLS_IO_CLIENT_ID="your_client_id"
export PROTOCOLS_IO_CLIENT_SECRET="your_client_secret"
export PROTOCOLS_IO_MCP_BASE_URL="https://example.com"
Run the MCP server with various transport options:
# Default: STDIO transport
protocols-io-mcp
# HTTP transport
protocols-io-mcp --transport http --host 127.0.0.1 --port 8000
# SSE transport
protocols-io-mcp --transport sse --host 127.0.0.1 --port 8000
Usage: protocols-io-mcp [OPTIONS]
Run the protocols.io MCP server.
Options:
--transport [stdio|http|sse] Transport protocol to use [default: stdio]
--host TEXT Host to bind to when using http and sse
transport [default: 127.0.0.1]
--port INTEGER Port to bind to when using http and sse
transport [default: 8000]
--help Show this message and exit.
To use this server with Claude Desktop, add the following configuration to your claude_desktop_config.json:
{
"mcpServers": {
"protocols-io": {
"command": "protocols-io-mcp",
"env": {
"PROTOCOLS_IO_CLIENT_ACCESS_TOKEN": "your_client_access_token"
}
}
}
}
This error indicates that Claude Desktop cannot find the protocols-io-mcp command. To resolve this:
protocols-io-mcp package globally using pip.command field in your claude_desktop_config.json to the full path of the protocols-io-mcp executable. You can find the path by running:
which protocols-io-mcp
{
"mcpServers": {
"protocols-io": {
"command": "/full/path/to/protocols-io-mcp",
"env": {
"PROTOCOLS_IO_CLIENT_ACCESS_TOKEN": "your_client_access_token"
}
}
}
}
Ensure you have set the PROTOCOLS_IO_CLIENT_ACCESS_TOKEN environment variable, then run:
pytest
This project is licensed under the MIT License. See the LICENSE file for details.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.