tiny-go-mcp-server
Minimal Go library for building stdio MCP servers on the official go-sdk — struct-derived JSON Schema, tiny static binaries.
README
Tiny Go MCP Server
A lightweight Model Context Protocol (MCP) toolkit for Go. Build spec-compliant, stdio-based MCP servers that AI clients can discover and call — with minimal boilerplate and automatic JSON Schema generation from Go structs.
Built on the official modelcontextprotocol/go-sdk.
Requirements: Go 1.26+ (download).
Why Tiny?
| Tiny Go MCP Server | Full frameworks | |
|---|---|---|
| Goal | Thin wrapper + tiny static binary | Full MCP feature surface |
| Deps | Official go-sdk only | Varies |
| Binary | ~5MB stripped, no runtime on host | Often larger stacks |
| Schemas | Inferred from struct tags | Manual or builder APIs |
Use this project as a library (tinymcp package) or as a starting template (cmd/tiny-go-mcp).
When to use what
| tinymcp (this repo) | mcp-go | go-sdk alone | |
|---|---|---|---|
| Best for | Thin wrapper, tiny binary, official SDK | Rich helpers, large ecosystem | Full control, no extra layer |
| Schema | Struct tags → auto JSON Schema | Builder APIs / helpers | AddTool + generics yourself |
| Transport | stdio via Start() |
stdio, SSE, HTTP, … | All transports |
| Deps | go-sdk only | Standalone module | go-sdk only |
Choose tinymcp when you want the official protocol implementation with minimal boilerplate and a small static server binary.
Transport
tinymcp.Start() runs stdio (stdin/stdout) — what Cursor, Claude Desktop, and most local clients expect. For HTTP, SSE, or custom transports, use server.RawServer() with the go-sdk directly.
Quick start (library)
go get github.com/kioie/tiny-go-mcp-server/tinymcp@latest
package main
import (
"context"
"fmt"
"log"
"github.com/kioie/tiny-go-mcp-server/tinymcp"
"github.com/modelcontextprotocol/go-sdk/mcp"
)
type greetArgs struct {
Name string `json:"name" jsonschema:"Person to greet"`
}
func main() {
s := tinymcp.NewServer("my-mcp", "1.0.0")
_ = tinymcp.RegisterTool(s, "greet", "Greet someone by name", greet)
log.Fatal(s.Start())
}
func greet(_ context.Context, _ *mcp.CallToolRequest, args greetArgs) (*mcp.CallToolResult, any, error) {
return tinymcp.TextResult(fmt.Sprintf("Hello, %s!", args.Name)), nil, nil
}
See examples/minimal for a runnable copy-paste example.
Install the example server
Both install paths produce a binary named tiny-go-mcp:
# Installs to $(go env GOPATH)/bin/tiny-go-mcp
go install github.com/kioie/tiny-go-mcp-server/cmd/tiny-go-mcp@latest
Or build from source (binary in the repo root):
git clone https://github.com/kioie/tiny-go-mcp-server.git
cd tiny-go-mcp-server
make release # → ./tiny-go-mcp
| Method | Binary name | Typical path |
|---|---|---|
go install …/cmd/tiny-go-mcp |
tiny-go-mcp |
$(go env GOPATH)/bin/tiny-go-mcp |
make build / make release |
tiny-go-mcp |
./tiny-go-mcp in the repo |
make install |
tiny-go-mcp |
$(go env GOPATH)/bin/tiny-go-mcp |
Example tools (reference server)
These tools exist for MCP integration demos, not production logic. Agents should compute math and write greetings in-chat unless they are explicitly testing tool calls.
| Tool | When to use | When not to / alternative | Arguments |
|---|---|---|---|
add |
Test that the client can call an addition tool | Real arithmetic → compute locally or use a calculator MCP | a, b |
subtract |
Test subtraction wiring (use instead of add for subtraction tests) |
Real arithmetic → compute locally | a, b |
greet |
Test a text-returning tool (use instead of add/subtract for messaging demos) |
User-facing hello → reply in the conversation | name (required), greeting (optional) |
Connect AI clients
MCP servers communicate over stdio. Point your client at the compiled binary path.
Template config: examples/mcp-client-config.json (copy and set the absolute path to tiny-go-mcp).
Logging: The protocol uses stdin/stdout. Server logs (if any) go to stderr only. Set TINY_GO_MCP_VERBOSE=1 on the server process to enable startup log lines.
Cursor
Settings → Features → MCP → Add server:
- Name:
tiny-go-mcp - Type:
stdio - Command:
/absolute/path/to/tiny-go-mcp
Or add to .cursor/mcp.json in your project:
{
"mcpServers": {
"tiny-go-mcp": {
"command": "/absolute/path/to/tiny-go-mcp"
}
}
}
Claude Desktop
~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"tiny-go-mcp": {
"command": "/absolute/path/to/tiny-go-mcp"
}
}
}
Windsurf / Zed / other stdio clients
Use the same shape: command = absolute path to tiny-go-mcp, transport = stdio. Refer to your client’s MCP docs for the config file location.
Tips for LLM-friendly tools
- Use clear tool names (
snake_case) and descriptions that say when to use, when not to, and which sibling tool applies — models pick tools from these and often have overlapping options. - Add
jsonschematags on struct fields so argument docs appear in the schema. - Return human-readable text via
tinymcp.TextResultfor predictable client display. - See AGENTS.md for conventions when extending this repo with AI assistants.
Package API
server := tinymcp.NewServer("name", "version")
tinymcp.RegisterTool(server, name, description, handler) // typed handler, auto schema
server.Start() // stdio transport
tinymcp.TextResult("message") // helper for text tools
server.RawServer() // escape hatch to go-sdk
Documentation: pkg.go.dev/github.com/kioie/tiny-go-mcp-server/tinymcp
Development
| Command | Description |
|---|---|
make test |
Run tests with race detector |
make lint |
golangci-lint |
make coverage |
Coverage report |
make build |
Dev binary ./tiny-go-mcp |
make release |
Stripped static binary |
make install |
go install → $(go env GOPATH)/bin/tiny-go-mcp |
Smaller binaries (~1.8MB)
After make release, optionally pack with UPX:
upx --best --lzma tiny-go-mcp
Project structure
tinymcp/ # Library package
cmd/tiny-go-mcp/ # Reference MCP server
examples/minimal/ # Minimal example
examples/mcp-client-config.json # Cursor/Claude-style template
docs/DISCOVERY.md # Registries and visibility
server.json # MCP Registry metadata (publish with mcp-publisher)
.github/workflows/ # CI, lint, CodeQL, releases
Releases
Tag a semver version (e.g. v1.0.0) to publish stable go get versions and trigger GitHub Releases with cross-platform binaries.
git tag v1.0.0
git push origin v1.0.0
Discovery and registries
See docs/DISCOVERY.md for MCP Registry (server.json), awesome lists, and community directories. For Glama hosting with Docker, see docs/GLAMA.md.
Contributing
See CONTRIBUTING.md. CI runs tests, lint, and CodeQL; Dependabot keeps Go and Actions dependencies updated.
License
MIT — see LICENSE.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.