MCP Server Copilot
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 CopilotRoute my request to find the latest stock prices."
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 Copilot
A meta Model Context Protocol (MCP) server that seamlessly scales LLMs to 1000+ MCP servers through automatic routing without expose all servers and tools to LLMs directly.
Components
Tools
router-servers: Route user query to appropriate MCP servers.query(string, required): User's query to find relevant servers.top_k(integer, optional): Maximum number of servers to return (default: 5).
route-tools: Route user query to appropriate MCP tools across all servers.query(string, required): User's query to find relevant tools.top_k(integer, optional): Maximum number of tools to return (default: 5).
execute-tool: Execute a specific tool on a specific server based on previous routing results.server_name(string, required): Name of the server hosting the tool.tool_name(string, required): Name of the tool to execute.params(object, optional): Parameters to pass to the tool, as a key-value dictionary (default: null or empty object).
Related MCP server: mcp-llm
Installation
Using uv (recommended)
When using uv no specific installation is needed. We will
use uvx to directly run mcp-server-copilot.
Using PIP
Alternatively you can install mcp-server-copilot via pip:
pip install mcp-server-copilotAfter installation, you can run it as a script using:
python -m mcp_server_copilotConfiguration
Copy config/config.sample.json to ~/.config/mcp-server-copilot
Add to your MCP Client settings:
{
"mcpServers": {
"copilot": {
"command": "uvx",
"args": ["mcp-server-copilot", "--config", "~/.config/mcp-server-copilot/config.json"]
}
}
}{
"mcpServers": {
"copilot": {
"command": "python",
"args": ["-m", "mcp_server_copilot", "--config", "~/.config/mcp-server-copilot/config.json"]
}
}
}TODOs
Add Dockerfile
Tune prompt and add show cases
Manage Servers more easily
Add Semantic Routing
Add Planning Capabilities
Resources & Prompts
Available Tools
3 toolsexecute-toolA
Execute a specific tool on a specific server based on previous routing results. Use this after you've identified the appropriate server and tool using the routing tools. This actually performs the requested operation.
| Name | Required | Description | Default |
|---|---|---|---|
| server_name | Yes | ||
| tool_name | Yes | ||
| params | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only says 'actually performs the requested operation' without detailing side effects, error handling, or prerequisites.
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?
Two sentences, front-loaded with purpose, no redundant information.
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?
Lacks details on success/failure behavior, error messages, or how to pass parameters, making it incomplete for an execution tool.
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?
Parameters have no schema descriptions (0% coverage). The description implies 'params' are tool arguments but provides no structure 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 explicitly states it executes a tool on a server based on routing results, clearly distinguishing it from routing siblings like 'router-servers' and 'route-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?
Explicitly states to use after routing tools, providing clear context for when to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
router-serversB
Route user query to appropriate servers. Use this when you need to find suitable servers that can handle the user's query. This should be your first step when processing a new query to determine which specialized servers are most relevant.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| top_k | 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 does not disclose behavioral traits like whether the operation is read-only, requires authentication, or has side effects. Only states routing but omits implications.
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?
Three sentences with clear front-loading: purpose first, then usage guidance, then additional context. No unnecessary words, though could be slightly more compact.
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 output schema and no parameter descriptions, the tool is incomplete. The agent cannot determine what the tool returns or how to use the parameters effectively, making it insufficient for confident selection and invocation.
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%, and the description fails to explain either parameter. 'query' and 'top_k' are not described beyond their types in the schema, leaving the agent with no guidance on their meaning or format.
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 tool's purpose: 'Route user query to appropriate servers.' It uses specific verb+resource and distinguishes from sibling tools by positioning it as the first step for finding relevant servers.
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 explicitly says 'Use this when you need to find suitable servers that can handle the user's query' and 'This should be your first step when processing a new query.' Provides clear context but does not list exclusions or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
route-toolsB
Route user query to appropriate tools across all servers. Use this when you need to find specific tools that can address the user's request, regardless of which server hosts them. This is helpful when you know the task type but not which server handles it.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| top_k | Yes |
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. It only states it routes queries but does not disclose behavioral traits such as whether it is read-only, performance characteristics, or what happens on errors. For a tool with no annotations, this is a significant gap.
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 concise at two sentences, front-loading the core purpose. It is well-structured and avoids unnecessary detail, though it could benefit from separating usage guidance from purpose.
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 absence of output schema, annotations, and parameter descriptions, the description is insufficiently complete. It does not specify the return format or how results are presented, leaving an AI agent with critical unknowns.
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%, and the description provides no explanation of the parameters ('query' and 'top_k'). Without any semantic guidance, an AI agent cannot infer what inputs are expected or how they affect behavior.
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 tool's purpose: routing a user query to appropriate tools across all servers. It effectively distinguishes from siblings like 'execute-tool' (execution) and 'router-servers' (server listing) by focusing on cross-server tool discovery.
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 clear when-to-use guidance: when you need to find tools for a request regardless of server, or when you know the task type but not the hosting server. It does not explicitly state when not to use or mention alternatives, but the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
3 tool updates
v0.1.4- First observed
execute-tool - First observed
route-tools - First observed
router-servers
TDQS
Scored across 3 tools
Each tool has a distinctly different purpose: one for finding servers, one for finding tools, and one for executing a tool. No overlap or ambiguity.
All names use lowercase with hyphens, but 'router-servers' uses a noun (router) while 'route-tools' uses a verb (route), introducing minor inconsistency.
Three tools is well-scoped for a routing/coordinating server, covering the essential functions without being too few or excessive.
Covers the core routing and execution workflow. A minor gap is the lack of a direct listing tool, but the routing tools subsume that functionality.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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