1MCP Server
Indicated by server-filesystem capability, which likely allows file operations on git repositories
Provides platform-specific configurations and file paths for Linux users
Provides platform-specific configurations and file paths for macOS users
Enables execution of shell commands through tagged server capabilities
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., "@1MCP Serverlist all my configured MCP servers and their status"
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.
1MCP
1MCP is the unified MCP runtime. 1mcp serve aggregates your MCP servers, and CLI mode adds a thinner agent-facing workflow for Codex, Claude, Cursor, and similar tool-using agents.
Why 1MCP
Most MCP setups eventually hit two kinds of sprawl:
Configuration sprawl: every client needs its own MCP wiring, auth choices, and filtering rules.
Agent sprawl: autonomous sessions carry too many tools and schemas into context up front.
1MCP addresses both:
1mcp servegives you one aggregated runtime in front of many MCP servers.CLI mode lets agents discover tools progressively with
instructions,inspect, andrun.Static servers can load at startup, while template servers are created from per-client or per-session context.
Presets, filters, and instruction aggregation keep the same runtime adaptable across clients and projects.
Approach | Best for | Tradeoff |
1MCP CLI mode | Codex, Claude, agent loops | Requires a running |
1MCP stdio proxy | Maximum compatibility across clients | Still depends on |
Direct streamable HTTP | MCP-native HTTP clients | No project context, no |
Custom proxying | One-off compatibility shims | You own discovery, filtering, auth, and runtime lifecycle |
Related MCP server: OpenRouter MCP Server
Quick Start for Agent Users
This page is optimized for AI agent users. The 5-minute outcome is simple: start a real 1mcp serve runtime, connect your agent with cli-setup, then verify the instructions -> inspect -> run workflow.
Install 1MCP, add one upstream server, and start the runtime:
npm install -g @1mcp/agent
1mcp mcp add context7 -- npx -y @upstash/context7-mcp
1mcp serveIn a second shell, connect your agent to CLI mode:
1mcp cli-setup --codex
# or
1mcp cli-setup --claude --scope repo --repo-root .Then verify the agent workflow:
# shell 1
1mcp serve
# shell 2
1mcp instructions
1mcp inspect context7
1mcp inspect context7/query-docs
1mcp run context7/query-docs --args '{"libraryId":"/mongodb/docs","query":"aggregation pipeline"}'If you want the full walkthrough (with success criteria and off-ramps), use the Quick Start guide.
For a given agent, choose one mode only. If you switch that agent to CLI mode, remove its old direct MCP configuration first.
Why CLI Mode Exists
CLI mode is the primary workflow for agent-style sessions. It keeps MCP as the backend protocol but narrows what the agent sees at each step:
instructionsexplains the current runtime and recommended flowinspectlets the agent discover only the server or tool it needsrunexecutes one selected tool after schema inspection
That gives agent loops a smaller working surface without giving up the unified runtime behind 1mcp serve.
Choose Another Path
Stdio Proxy
Use 1mcp proxy when you want the broadest client compatibility without giving up project context.
It is the recommended fallback after CLI mode because it:
works with the stdio transport that most AI clients already support
keeps project context through
.1mcprcsupports template MCP servers resolved from project or session context
is easier to roll out with one-time global setup plus per-project config
Direct stdio mode is not the recommended path. It is mainly useful for debugging because 1MCP startup is slower than a thin standalone stdio setup.
Direct MCP Attachment
Direct MCP attachment is still supported for clients that want to talk to the aggregated runtime over streamable HTTP.
Examples:
{
"mcpServers": {
"1mcp": {
"url": "http://127.0.0.1:3050/mcp?app=cursor"
}
}
}claude mcp add -t http 1mcp "http://127.0.0.1:3050/mcp?app=claude-code"Use this path if your client already speaks MCP natively, can work without project context, and you do not want CLI mode. For Codex, Claude, Cursor, and similar agent loops, prefer CLI mode first and proxy second.
Runtime Operators
Use the deeper docs if you are configuring or deploying the runtime itself:
Contributors
How It Works
flowchart LR
A[User or Agent] --> B[1mcp serve]
B --> C[Static servers loaded at startup]
B --> D[Template servers resolved from client or session context]
A --> E[CLI mode: instructions -> inspect -> run]
E --> B
F[Direct streamable HTTP client] --> B
G[stdio-compatible client] --> H[1mcp proxy]
H --> B1MCP runs as an aggregated runtime behind 1mcp serve. Static servers are prepared from startup configuration, template servers are materialized when client context is known, and the runtime can use async loading and lazy loading to reduce startup blocking and tool-surface noise. Instruction aggregation, presets, and notifications sit alongside that runtime rather than outside it.
Core Capabilities
Unified runtime for many MCP servers behind one
serveprocessCLI mode for progressive discovery with
1mcp instructions,1mcp inspect <server>,1mcp inspect <server>/<tool>, and1mcp run <server>/<tool> --args '<json>'Template servers for per-client or per-session resolution
Async loading and lazy loading for faster startup and narrower exposure
Instruction aggregation across static and template-backed servers
Presets, filters, and preset change notifications
proxyfor maximum compatibility with project context and template-server supportDirect streamable HTTP MCP access for native HTTP clients that do not need project context
Common Use Cases
Give a coding agent one stable runtime but a smaller working surface.
Share the same MCP inventory across Cursor, Claude Code, Codex, and internal tooling.
Expose context-specific template servers per repo, branch, or session.
Centralize auth, filtering, presets, and runtime lifecycle instead of rebuilding them in ad hoc scripts.
Contributing / License
Contributions are welcome. See CONTRIBUTING.md for the development workflow and LICENSE for the Apache 2.0 license.
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Maintenance
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