Route one agent through one MCP server to many, with progressive tool discovery to shrink context.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

Every MCP server you connect costs context before the agent does anything β its tool manifests sit in the prompt on every turn. McpOrchestrator puts one server between your agent and all the others and loads downstream tool manifests on demand, so the agent's always-on context stays flat no matter how many servers you add. The agent sees three meta-tools β list_capabilities β discover_tools β route β and the orchestrator is a pure relay: it forwards exactly what the agent sends, never interpreting it. It can also serve Agent Skills with the same on-demand discipline.
https://github.com/user-attachments/assets/741c1afa-4bef-4870-9b84-e2c245b8117e
Against a real workplace MCP setup, measured with the Copilot CLI's /usage:
| Tokens in context | |
|---|---|
| MCP connected directly (manifests loaded upfront) | 17,900 |
| Same MCP behind McpOrchestrator | 1,400 |
| Reduction | ~13x |
The savings scale with the number of servers. Measure your own setup first β one command, nothing installed, not a single file changed (needs the .NET SDK):
From an existing MCP setup, cd to the folder holding your host config (.mcp.json, .vscode/mcp.json, or a Cursor config) and run:
It lifts your stdio servers into a generated orchestrator.config.json, backs up the host config, and rewrites it to launch only the orchestrator. The generated catalog looks like this β one entry per downstream server:
The summary line is what the agent routes on β refine any that read poorly. Restart your MCP host and you're done: the agent discovers everything on its own through list_capabilities β discover_tools β route, and every later edit to this file hot-reloads without a restart.
A skill is a folder with a SKILL.md β instructions the agent discovers and follows by itself when a task matches. Create one:
Point the orchestrator at the folder in orchestrator.config.json:
Save β it hot-reloads. The agent now sees the skill's name + one-line description via list_skills and loads the full instructions only when a task calls for it. Skills can also come from a shared git repo or an HTTP index, with allow/deny lists and integrity pinning β see docs/skills.md.
Note: these skills are for the agent only β the model discovers and follows them through tools. They do not become host-native skills (no
/skillslisting or slash command in Claude Code, no IDE skill picker entry).
Everything else lives in McpOrchestrator/README.md and docs/:
profile command in depth, trace mode, CI gatinginit, and profile, plus all environment variablesinit generates, written by handShowcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.
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