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 custom MCP server exposing 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
Got: YAML or markdown spec for each tool with name, description, parameters (types, defaults, required flags), return type documented before writing code.
If fail: Tool specifications unclear? Interview domain expert or review existing API documentation for 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);
Got: Working server.js imports MCP SDK, defines tools with Zod schemas, connects via stdio transport. Running node server.js starts server without errors.
If fail: Verify @modelcontextprotocol/sdk and zod installed (npm install). Check import paths match SDK version (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()
Got: Working server.R registers custom tools with mcp_tool(), starts server with mcp_server(). Running Rscript server.R starts MCP server.
If fail: Ensure mcptools installed from GitHub (remotes::install_github("posit-dev/mcptools")). Check handler function signatures match 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
Got: Project directory created with server.js (or server.R), package.json, tools/ directory for modular tool implementations, test/ for tests.
If fail: Directory structure doesn't match 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 Claude Code session, check custom tools listed and functional.
Got: tools/list JSON-RPC call returns all defined tools with correct names and schemas. claude mcp list shows server registered. Tools callable from Claude Code session.
If fail: tools/list returns empty array? Tools were not registered before server.connect(). Claude Code cannot find server? Verify command path in claude mcp add is absolute, 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,
};
}
});
Got: Each tool handler wrapped in try/catch. Invalid inputs return isError: true with descriptive message instead of crashing server process.
If fail: Server still crashes on bad input? Check try/catch wraps entire handler body including async operations. Ensure promises awaited within try block.
Create package.json with 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 install and configure:
npm install -g my-mcp-server
claude mcp add my-server stdio "my-mcp-server"
Got: package.json with bin entry pointing to server entry point. Users install globally with npm install -g, register with claude mcp add.
If fail: Bin entry doesn't work after global install? Ensure server.js has shebang line (#!/usr/bin/env node), is marked executable. Verify package name doesn't conflict with existing npm packages.
tools/list returns all defined tools with correct schemasconfigure-mcp-server - connect built server to clientstroubleshoot-mcp-connection - debug connectivity issuescontainerize-mcp-server - package server in Docker