Discorevy local MCP Servers. Specification.
LocalAbout Discorevy local MCP Servers. Specification.
Discorevy local MCP Servers is a specification for listing and configuring MCP servers on a local machine. MCP clients discover Markdown descriptions in `~/.mcp` and use an LLM to interpret them; server security remains the client’s responsibility.
Key features
- 01Store one Markdown file per server
- 02Discover files in `~/.mcp`
- 03Describe server details for LLM interpretation
- 04Refresh local server descriptions
Use cases
- 01Standardize local MCP server registration
- 02Help a client discover available servers
- 03Describe when a server may fit a request
MCP support
The specification describes how MCP clients discover local server descriptions and use an LLM to interpret them as actionable MCP servers. It does not define server security.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEmcp-server-1.com
Welcome!
AI agents open great opportunities and enables so many new possibilities. Below is just one of the examples. so far the Agent Skills protocol look very promising, read about it here https://agentskills.io/home.
Follow me on X and LinkedIn to learn more about the ideas and cutting edge experiments.
https://www.linkedin.com/in/jonnyzzz
Discorevy local MCP Servers. Specification.
Version: 1.0.1
Goals
This specification aims to allow the standard way to list and configure MCP Servers on a local machine.
Many tools already use MCP Servers to augment the LLMs. Currently, there is no standard approach to quickly registering an MCP Server.
Here are the most popular MCP Clients:
- IntelliJ IDEA
- Anthropic Claude
- OpenAI ChatGPT
- Cursor
- Windsurf
- Warp
- PR to add you
Supported in the following tools
- PR if you support the spec
Specification
Create a file per each MCP server in the ~/.mcp folder (%USER_HOME% on Windows).
The file is a Markdown file that explains an LLM (such as Claude or CharGPT) about your MCP Server details. The client uses LLM to transform your explanation into an actionable MCP Server.
The client is required to regularly refresh the information from the disc to discover new MCP Servers.
This protocol does not resolve any security implications for MCP servers. That is still the responsibility of MCP Clients.
For example:
~/.mcp/my-mcp-server-tool-id.md
Create the following text inside:
---
version: 1.0.1
---
# MCP Server: Production
Here, I describe what my MCP Server is doing and why the LLM would decide to include my server in a specific request, which is queried.
## Basic Information
- **Name**: Production Jonnyzzz MCP Server
- **ID**: prod-mcp-01
- **Version**: 3.2.1
- **URL**: https://mcp-prod.jonnyzzz.com:8443
- **API Version**: v2
## Authentication
- **Type**: oauth2
- **Client ID**: client_123
- **Token Endpoint**: https://auth.example.com/token
## Capabilities
- compute
- storage
- networking
## Regions
### us-east
- us-east-1a
- us-east-1b
### eu-west
- eu-west-1a
- eu-west-1b
## Health Check
- **Endpoint**: /health
- **Interval**: 60 seconds
## Metadata
- **Environment**: production
- **Owner**: platform-team
- **Priority**: high
How to use the Spec?
An MCP client uses the LLM (e.g., Claude, ChatGPT) to extract the necessary information from each of the available MCP server's markdown files, which are discovered in the files under the ~/.mcp folder.
It is up to the LLM and the client to decide if to use a specific LLM, ask for credentials, and so on.
The client should refresh the files from the disk regularly.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.