A tiny, local-first AI harness for people who prefer a terminal.
One static binary. Zero dependencies. No TUI. No telemetry. MIT.

Why Shim?

Model-agnostic coding agents are everywhere. Setting them up is still too hard: provider IDs, API endpoints, MCP JSON, skills directories, and a new interface for every tool.

Shim is the small adapter between you and all of that.

• Talk or type commands. A full scriptable CLI for experts; ordinary language for everyone else.
• Use a local mini-model as the command router. It translates management requests into an allowlisted command. Mutating commands require confirmation.
• Bring any model API. Native OpenAI-compatible and Anthropic adapters, plus presets for popular hosted and local providers.
• Bring any MCP server or Agent Skill. MCP over stdio and Streamable HTTP; lazy SKILL.md loading from common directories.
• Stay light. No Electron, Node, Python, Docker, database, background daemon, or UI framework.
• Own your state. Plain JSON config and JSONL sessions. API keys come from environment variables and are never written to Shim's config.

Measured on the maintainer's Windows machine for v0.1.0: 7.29 MiB stripped binary and 9.96 ms median process startup for shim --version over 30 runs. This is a local measurement, not a cross-platform performance guarantee.

Install

Download

Get a static binary for Windows, macOS, or Linux from Releases, put it on your PATH, then run:

shim setup
shim

On PowerShell, use .\shim.exe when running the binary from the current directory.

With Go

Go 1.25+:

go install github.com/Balanov/shim/cmd/shim@v0.1.0
shim setup

From source

git clone https://github.com/Balanov/shim.git
cd shim
go test ./...
go build -trimpath -ldflags="-s -w" -o shim ./cmd/shim
./shim setup

Windows also has scripts/build.ps1; Unix has scripts/build.sh.

Two ways to use it

Just talk

you › найди локальные модели
↳ /discover --add
Run this command? [y/N] y

you › show my tools
↳ /tools

you › fix the failing tests in this repository

Shim has deterministic offline phrases for common English and Russian management commands. For other languages, assign a local model as the router:

shim router use ollama/qwen3:4b

The router sees non-command chat text so it can distinguish configuration requests from agent tasks. Use a loopback model if you want that step to stay on your machine. No model weights are bundled or silently downloaded; that would defeat the tiny-binary goal. Your primary model handles ordinary conversation in whatever language it supports.

Use the complete CLI

# Local models: discover and configure all running servers
shim model discover --add

# Hosted models
shim model add openrouter anthropic/claude-sonnet-4.5 --name claude --use
shim model add openai gpt-5 --name gpt --use
shim model add huggingface org/model --name hf --use

# Any OpenAI-compatible endpoint
shim model add custom my-model --name mine \
  --base-url http://127.0.0.1:8000/v1 --use

# One-shot agent run
shim run --read-only "explain this repository"
shim run --yes --verbose "fix the tests and verify the result"

# Interactive terminal
shim

Run shim help for the full command surface.

Model providers

Preset	Adapter	Credential environment variable
ollama	OpenAI-compatible	None
lmstudio	OpenAI-compatible	None
llamacpp	OpenAI-compatible	None
openai	OpenAI-compatible	OPENAI_API_KEY
openrouter	OpenAI-compatible	OPENROUTER_API_KEY
anthropic	Anthropic Messages	ANTHROPIC_API_KEY
gemini	Gemini OpenAI-compatible endpoint	GEMINI_API_KEY
github	GitHub Models	GITHUB_TOKEN
huggingface	Hugging Face router	HF_TOKEN
custom	OpenAI-compatible or Anthropic	Optional, configurable

“Any model” means any model exposed through a supported HTTP API. GGUF and other local weights run through Ollama, LM Studio, llama.cpp, or another compatible inference server; Shim is the harness, not an inference engine.

PowerShell example:

$env:OPENROUTER_API_KEY = "..."
shim model add openrouter your/model --name main --use
shim model test main

For persistent environment variables, use your OS or shell's standard secret/configuration mechanism. Do not put keys in the project config.

Skills

Shim discovers SKILL.md in:

• the global skills/ directory next to Shim's config;
• .shim/skills/;
• .agents/skills/;
• .claude/skills/.

Only names and descriptions enter the system prompt. Full instructions load on demand through load_skill.

shim skill add owner/repository
shim skill add https://github.com/owner/repository
shim skill add ./local/skill-or-collection
shim skill list
shim skill show name
shim skill remove name

Skills are untrusted instructions. Review them before use, especially when they request shell or network access.

MCP

# Stdio server
shim mcp add filesystem npx -y @modelcontextprotocol/server-filesystem .
shim mcp tools filesystem
shim mcp call filesystem list_allowed_directories '{}'

# Streamable HTTP server
shim mcp add internal https://mcp.example.com/mcp

shim mcp list
shim mcp remove filesystem

MCP tools are namespaced as mcp_<server>_<tool> and require confirmation in the default ask mode. HTTP headers and stdio environment variables can be added to the JSON config. Values support ${ENV_VAR} expansion, so secrets can stay in the environment rather than in files.

Permissions and safety

Default mode is ask:

• reading, listing, and searching workspace files: allowed;
• writing/editing files, shell commands, and MCP calls: confirmation required;
• file tools reject lexical traversal and symlink escapes from the workspace.

shim permissions read-only  # no writes, shell, or MCP
shim permissions ask        # confirm consequential actions
shim permissions auto       # allow the agent to act without prompts

For one run, prefer --read-only or --yes over changing the global default.

Shim is not an OS sandbox. Shell commands and MCP servers run with your user's permissions. Workspace path checks do not contain a malicious process. Use a container, VM, or OS sandbox for untrusted workloads. Treat model output, repository text, skills, and MCP responses as untrusted data.

Sessions and configuration

shim session list
shim session new
shim run --resume SESSION_ID "continue"
shim status
shim doctor
shim config path
shim config show

Config is at the OS user-config location in shim/config.json; override it with SHIM_CONFIG or --config. Sessions are append-only JSONL next to it. Network traffic occurs only for explicit model calls, skill downloads, local discovery, and the MCP servers you configure.

What Shim deliberately is not

Project	Strength	Shim's different bet
OpenCode	Full-featured provider-agnostic terminal workspace	No TUI/server surface; conversational setup and a tiny static binary
Pi	Minimal, extensible coding-agent toolkit	Zero runtime dependencies and an allowlisted natural-language control layer
Goose	Broad MCP-powered automation ecosystem	A smaller local-first control plane with no daemon or desktop app
Aider	Git-native pair programming	General agent harness with MCP, lazy skills, and conversational management

Shim does not try to beat foundation-model vendors at their own agent UI. It makes heterogeneous models and tools easy to wire together and easy to fork.

Development

go test ./...
go vet ./...
go fmt ./...

The codebase uses only the Go standard library. See Architecture, Contributing, and Security. Русское введение: README_RU.md.

Roadmap

• streaming token output and cancellation polish;
• OS-level sandbox profiles;
• OAuth helpers for remote MCP;
• context compaction and richer session export;
• additional deterministic language packs and provider conformance tests.

License

MIT. Fork it, modify it, embed it, ship it.