brainstorming
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or planning anything new, in software or out of it (a talk, a business, a renovation).
build-custom-mcp-serverBuild a custom MCP (Model Context Protocol) server that exposes domain-specific tools to AI assistants. Covers server implementation in Node.js or R, tool definitions, transport configuration, and testing with Claude Code. Use when you need to expose custom functionality beyond what mcptools provides, when building specialized domain-specific AI integration…
Independent GitHub snapshot · Automated classification · Original documentation governs
Create a custom MCP server that exposes domain-specific tools to AI assistants.
Before writing code, define each tool:
tools:
- name: query_database
description: Execute a read-only SQL query against the analysis database
parameters:
query:
type: string
description: SQL SELECT query to execute
required: true
limit:
type: integer
description: Maximum rows to return
default: 100
returns: JSON array of result rows
- name: run_analysis
description: Execute a predefined statistical analysis by name
parameters:
analysis_name:
type: string
description: Name of the analysis to run
enum: [descriptive, regression, survival]
dataset:
type: string
description: Dataset identifier
required: true
预期结果: A YAML or markdown specification for each tool with name, description, parameters (including types, defaults, and required flags), and return type documented before writing any code.
失败处理: If tool specifications are unclear, interview the domain expert or review the existing API documentation to determine parameter types and return formats.
// server.js
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "my-analysis-server",
version: "1.0.0",
});
// Define tools
server.tool(
"query_database",
"Execute a read-only SQL query against the analysis database",
{
query: z.string().describe("SQL SELECT query"),
limit: z.number().default(100).describe("Max rows to return"),
},
async ({ query, limit }) => {
// Validate read-only
if (!/^\s*SELECT/i.test(query)) {
return {
content: [{ type: "text", text: "Error: Only SELECT queries allowed" }],
isError: true,
};
}
const results = await executeQuery(query, limit);
return {
content: [{ type: "text", text: JSON.stringify(results, null, 2) }],
};
}
);
server.tool(
"run_analysis",
"Execute a predefined statistical analysis",
{
analysis_name: z.enum(["descriptive", "regression", "survival"]),
dataset: z.string().describe("Dataset identifier"),
},
async ({ analysis_name, dataset }) => {
const result = await runAnalysis(analysis_name, dataset);
return {
content: [{ type: "text", text: JSON.stringify(result, null, 2) }],
};
}
);
// Start server with stdio transport
const transport = new StdioServerTransport();
await server.connect(transport);
预期结果: A working server.js file that imports the MCP SDK, defines tools with Zod schemas, and connects via stdio transport. Running node server.js starts the server without errors.
失败处理: Verify that @modelcontextprotocol/sdk and zod are installed (npm install). Check that the import paths match the SDK version (the SDK reorganized exports between versions).
# server.R
library(mcptools)
# Register custom tools
mcp_tool(
name = "query_database",
description = "Execute a read-only SQL query",
parameters = list(
query = list(type = "string", description = "SQL SELECT query"),
limit = list(type = "integer", description = "Max rows", default = 100)
),
handler = function(query, limit = 100) {
if (!grepl("^\\s*SELECT", query, ignore.case = TRUE)) {
stop("Only SELECT queries allowed")
}
result <- DBI::dbGetQuery(con, paste(query, "LIMIT", limit))
jsonlite::toJSON(result, auto_unbox = TRUE)
}
)
# Start server
mcptools::mcp_server()
预期结果: A working server.R file that registers custom tools with mcp_tool() and starts the server with mcp_server(). Running Rscript server.R starts the MCP server.
失败处理: Ensure mcptools is installed from GitHub (remotes::install_github("posit-dev/mcptools")). Check that the handler function signatures match the parameter definitions.
my-mcp-server/
├── package.json # Node.js dependencies
├── server.js # Server implementation
├── tools/ # Tool implementations
│ ├── database.js
│ └── analysis.js
├── test/ # Tests
│ └── tools.test.js
├── Dockerfile # Container packaging
└── README.md # Setup instructions
预期结果: Project directory created with server.js (or server.R), package.json, tools/ directory for modular tool implementations, and test/ directory for tests.
失败处理: If the directory structure doesn't match your implementation language, adjust accordingly. R servers may use R/ instead of tools/ and tests/testthat/ instead of test/.
Manual testing with stdio:
echo '{"jsonrpc":"2.0","method":"tools/list","id":1}' | node server.js
Register with Claude Code:
claude mcp add my-server stdio "node" "/path/to/server.js"
Verify tools appear:
Start a Claude Code session and check that custom tools are listed and functional.
预期结果: The tools/list JSON-RPC call returns all defined tools with correct names and schemas. claude mcp list shows the server registered. Tools are callable from a Claude Code session.
失败处理: If tools/list returns an empty array, the tools were not registered before server.connect(). If Claude Code cannot find the server, verify the command path in claude mcp add is absolute and the binary is executable.
server.tool("risky_operation", "...", schema, async (params) => {
try {
const result = await performOperation(params);
return {
content: [{ type: "text", text: JSON.stringify(result) }],
};
} catch (error) {
return {
content: [{ type: "text", text: `Error: ${error.message}` }],
isError: true,
};
}
});
预期结果: Each tool handler is wrapped in try/catch. Invalid inputs return isError: true with a descriptive message instead of crashing the server process.
失败处理: If the server still crashes on bad input, check that the try/catch wraps the entire handler body including any async operations. Ensure promises are awaited within the try block.
Create a package.json with a bin entry:
{
"name": "my-mcp-server",
"version": "1.0.0",
"bin": {
"my-mcp-server": "./server.js"
},
"dependencies": {
"@modelcontextprotocol/sdk": "^1.0.0",
"zod": "^3.22.0"
}
}
Users can then install and configure:
npm install -g my-mcp-server
claude mcp add my-server stdio "my-mcp-server"
预期结果: A package.json with a bin entry pointing to the server entry point. Users can install globally with npm install -g and register with claude mcp add.
失败处理: If the bin entry doesn't work after global install, ensure server.js has a shebang line (#!/usr/bin/env node) and is marked executable. Verify the package name doesn't conflict with existing npm packages.
tools/list returns all defined tools with correct schemasconfigure-mcp-server - connect the built server to clientstroubleshoot-mcp-connection - debug connectivity issuescontainerize-mcp-server - package the server in Docker