Open-source Go runtime for AI agents
Built for the age of agent teams, not just single agents.
💬 Discussions · 🐛 Issues · 🖥️ seshat-ai
The agentic AI space is moving fast. Dozens of frameworks have emerged — LangChain, LangGraph, CrewAI, AutoGen, and many others. Almost all of them are Python-first. That works fine for experimentation, but it creates real friction the moment you want to ship something: dependency hell, slow startup, heavy containers, difficult embedding in existing services.
⚡ Go changes the equation. A single statically linked binary. No runtime, no venv, no dependency manager. Low latency, predictable memory, easy deployment anywhere — from a Raspberry Pi to a Kubernetes cluster. Seshat brings that to agentic AI.
But the choice of language is the smaller part of the story.
Individual agents have become impressive. They can reason for hours, use tools, write code, search the web, produce deliverables. The frontier has moved. The hard unsolved problem is no longer what a single agent can do — it is how multiple agents can work together in a coherent, observable, and economically useful way.
Most current systems handle this with pipelines, handoffs, or orchestration graphs. These are useful, but they remain technical constructs. They don't model work the way humans actually do it.
We believe the right model for agent collaboration is not the workflow graph — it is the human organization.
Real teams don't communicate through function calls. They have roles, responsibilities, inboxes, meetings, status reports, shared decisions, and a working memory of the mission. A project lead delegates tasks. A specialist delivers a report. A reviewer pushes back. A coordinator synthesizes. Information flows explicitly. Decisions are recorded. Nothing is lost in a black-box state machine.
Seshat is being built around this idea: study how humans work in teams — in companies, research groups, or any collaborative setting — and reproduce those coordination patterns with autonomous agents.
This means agents that:
- 📬 communicate through structured messages, not just function calls
- 📋 can send a report, schedule a review, claim a task, or escalate a blocker
- 🧩 have an identity, a role, and a history — not just a prompt and a response
- 🗂️ share a mission memory that keeps decisions, constraints, and objectives alive across the team
We are building the foundation. Seshat today is a solid, production-grade runtime: persistent sessions, 60+ tools, 15 LLM providers, MCP client, RAG, skills, gRPC API, sandboxed execution. It is already useful as a standalone CLI, an embeddable Go SDK, or the engine behind seshat-ai.
The team primitives (mailboxes, roles, missions, structured inter-agent communication) are the next major layer. We are designing them now, informed by how real organizations function.
This is an open research and engineering project as much as a software one. The ecosystem we want to build is ambitious, and no single perspective has all the answers.
If you have ideas about how agents should collaborate, how human team structures map to agentic systems, what organizational patterns are worth modeling, or what the ecosystem is still missing: your input is genuinely valuable.
👉 Open a Discussion, an issue, or a PR. Every suggestion is read.
We are building this together. 🚀
seshat chat drops you into a full-featured terminal interface built for long-running agent sessions.
Keyboard shortcuts:
ctrl+psettings ·ctrl+mmodels ·ctrl+ssessions ·ctrl+,providers ·ctrl+nnew session ·ctrl+ttasks ·ctrl+ucopy last response ·ctrl+ytoggle yolo ·ctrl+oopen editor ·ctrl+ghelp ·ctrl+cquit
Clipboard note (Linux): selection copy works best when
wl-clipboard(Wayland) orxclip/xsel(X11) is installed. Without a system clipboard backend, Seshat can request terminal clipboard access but cannot guarantee a real system copy.
Compaction note: transcript compaction is automatic today. A dedicated manual compact action is planned for the TUI once the runtime exposes a real manual-compaction hook.
seshat is the headless runtime: pure Go, no UI, no users, no billing. It is the foundation everything else builds on.
→ seshat-ai is the full production platform built on top of this engine. If you want a ready-to-use application rather than a library, that is where you want to go.
| seshat (this repo) | seshat-ai | |
|---|---|---|
| What it is | Go runtime + SDK + CLI | Desktop app + REST API platform |
| Stack | Go | Go (API) + TypeScript/React/Electron (desktop) |
| License | Apache 2.0 | AGPL-3.0 |
| Who it's for | Developers embedding agents in their own apps | End users, teams, self-hosters |
| Includes | Engine, tools, providers, gRPC, CLI/TUI | Multi-user auth, workspaces, knowledge base, scheduler, desktop UI |
What seshat-ai gives you today:
- 🖥️ Native desktop app (Electron + React) with chat, tool views, plans, settings and a visual skills creator
- 👥 Multi-user backend with organizations, workspaces, per-user API keys, quotas and audit log
- 📡 REST + SSE HTTP API compatible with the Anthropic
/v1/messagesformat - 📚 Knowledge base with hybrid BM25 + vector search and file ingestion
- ⏰ Scheduled tasks, memories, plans and MCP server management
Coming next:
- 🤝 Agent teams: persistent groups of specialized agents collaborating on shared missions, each with its own inbox, role and memory
- 🤖 Automation and background workflows triggered by schedule, events or voice
- 🖼️ Image generation integrated directly into the chat and workspace
- 🎙️ Voice input and audio output so you can talk to your agents naturally
- 🌐 A multi-workspace environment covering code, research, creation and learning, all sharing the same runtime and data layer
| If you want to... | Contribute to... |
|---|---|
| Improve execution speed, reduce latency, optimize the agent loop | seshat (Go) |
| Add a new LLM provider or tool | seshat (Go) |
| Expose new capabilities in the SDK or gRPC API | seshat (Go) |
| Improve the desktop UI, add new views, fix UX | seshat-ai (TypeScript/React) |
| Build features like agent teams, automation or scheduling | seshat-ai (Go API + React) |
The engine is intentionally kept minimal and fast. If you need something from the SDK that is not exposed yet, open an issue and we will prioritize it.
End users — one command, fully configured:
curl -fsSL https://raw.githubusercontent.com/EngineerProjects/seshat/main/scripts/install.sh | bashDownloads the right binary for your platform, adds it to your PATH, installs uv and docling-serve for document processing, and leaves the runtime directory (~/.config/seshat-cli/) ready. The DB and sessions are created on first run.
Options:
NO_PYTHON=1 bash <(curl -fsSL ...) # skip uv + docling (minimal install)
VERSION=v0.1.0 bash <(curl -fsSL ...) # pin a specific versionDevelopers — Go toolchain:
# Install the CLI binary
go install github.com/EngineerProjects/seshat/cmd/cli@latest
# Then set up document processing if needed
seshat setup
# Or check what is already installed
seshat setup --checkSDK — embed in your Go application:
go get github.com/EngineerProjects/seshat@latestAn AI agent in your terminal. Multi-provider, local-first, skills-aware.
Install
# End users — full setup in one command:
curl -fsSL https://raw.githubusercontent.com/EngineerProjects/seshat/main/scripts/install.sh | bash
# Developers — binary only via Go toolchain:
go install github.com/EngineerProjects/seshat/cmd/cli@latest
seshat setup # install uv + docling-serve afterwards if needed
seshat setup --check # check what is already configuredConfigure a provider
seshat config --provider anthropic --api-key sk-ant-...
seshat config --model anthropic:claude-sonnet-4-20250514
seshat config --printRun
seshat chat # interactive TUI session
seshat chat --resume <session-id> # resume a specific session
seshat chat --continue # resume the most recent session
seshat run "list all TODO comments in this codebase" # one-shot task
seshat sessions list # browse past sessions
seshat setup --check # show uv / docling status
seshat version # print installed version
seshat help # full command referenceSessions are persisted locally in SQLite. Skills are loaded from .seshat/skills/ in your project. The full tool set is available: file edits, sandboxed bash, web search, browser, MCP servers, sub-agents.
Run seshat as a gRPC service and generate clients for any language.
# Development
ANTHROPIC_API_KEY=sk-ant-... go run ./cmd/grpc
# From build
ANTHROPIC_API_KEY=sk-ant-... ./bin/seshat-grpcServer starts on :50051. The contract lives in pkg/grpc/proto/nexus.proto. Generate a client for Python, TypeScript, Java, Rust, or any gRPC-supported language:
# Python
python -m grpc_tools.protoc -I pkg/grpc/proto --python_out=. --grpc_python_out=. nexus.proto
# TypeScript
npx grpc-tools --js_out=. --grpc_out=. pkg/grpc/proto/nexus.protoOne runtime. Every language.
Embed the full runtime in your own Go application.
go get github.com/EngineerProjects/seshat/pkg/sdkimport "github.com/EngineerProjects/seshat/pkg/sdk"
client, err := sdk.NewClient(&sdk.ClientConfig{
APIKey: os.Getenv("ANTHROPIC_API_KEY"),
Model: sdk.ModelIdentifier{Provider: "anthropic", Model: "claude-sonnet-4-20250514"},
})
if err != nil {
log.Fatal(err)
}
defer client.Close()
session, _ := client.CreateSession(ctx)
resp, _ := session.SubmitMessage(ctx, "Write a Go HTTP handler for /health")
fmt.Println(resp.Content)| Feature | seshat | Claude Agent SDK | OpenAI Agents SDK | LangGraph | CrewAI |
|---|---|---|---|---|---|
| Language | Go | Python/TS | Python | Python | Python |
| Single binary (no deps) | ✅ | ❌ | ❌ | ❌ | ❌ |
| CLI included | ✅ | ❌ | ❌ | ❌ | ❌ |
| gRPC server (any language) | ✅ | ❌ | ❌ | ❌ | ❌ |
| Multi-provider | ✅ (15) | ❌ Claude only | ❌ OpenAI only | ✅ | ✅ |
| MCP client | ✅ | ✅ | ✅ | Partial | ❌ |
| Sandboxed bash (Landlock) | ✅ | ✅ | ❌ | ❌ | ❌ |
| Skills system | ✅ | ❌ | ❌ | ❌ | ❌ |
| Built-in RAG | ✅ | ❌ | ❌ | ❌ | ❌ |
| Browser automation | ✅ | ✅ | ❌ | ❌ | ❌ |
| Session persistence | ✅ | ❌ | ❌ | ✅ | ❌ |
| OTel tracing | ✅ | ❌ | ❌ | ✅ | ❌ |
| Open-source license | Apache 2.0 | MIT | MIT | MIT | Apache 2.0 |
| Capability | Details |
|---|---|
| 🌍 Multi-provider | 15 providers: Anthropic, OpenAI, Gemini, Mistral, DeepSeek, Ollama, OpenRouter, AWS Bedrock, GCP Vertex, Azure Foundry, Codex, MiniMax, Z.ai, OpenCode, Cloudflare Workers AI |
| 🛠️ 60+ built-in tools | File read/write/patch, bash (Landlock sandbox), web search, web fetch, browser (Playwright), grep/glob, LSP, sub-agents, RAG, tasks, memory, worktree, notebooks, image generation, TTS/STT |
| 🔌 MCP client | Universal MCP client: plug in any MCP server (GitHub, Postgres, Slack, Docker, Notion, ...) |
| ⚡ Skills | Markdown instruction files injected into the system prompt: encode your team's conventions and domain expertise |
| 🎯 Execution modes | execute (default), plan (review before act), pair_programming (collaborative) |
| 🔒 Permission engine | Per-tool deny rules, auto-mode LLM classifier, configurable per session (auto / acceptEdits / onRequest / bypass / never) |
| 💾 Session persistence | SQLite-backed multi-turn sessions, resumable across restarts |
| 📡 Streaming | Text chunks + structured runtime events (tool calls, plan events, permission requests, token usage) |
| 🧠 Long-context compaction | Automatic context compression when approaching the model's window (configurable threshold) |
| 📉 Observability | Prometheus metrics + OpenTelemetry tracing (OTLP gRPC export, no-op when endpoint not set) |
seshat/
├── cmd/
│ ├── cli/ ← seshat CLI entrypoint (TUI + one-shot commands)
│ └── grpc/ ← gRPC server entrypoint
├── pkg/ ← public API (safe to import from outside)
│ ├── sdk/ ← Go SDK: Client, sessions, streaming, callbacks
│ ├── types/ ← shared types: Message, ToolUse, TokenUsage, ...
│ ├── agent/ ← agent definitions, built-in registry
│ ├── providers/ ← LLM provider abstraction, routing, fallback
│ ├── mcp/ ← MCP client: stdio, SSE, HTTP transports
│ ├── rag/ ← chunking, embedding, hybrid vector search
│ ├── skills/ ← skill loading, frontmatter parsing, injection
│ ├── memory/ ← in-session state, compaction strategies
│ ├── web/ ← web search, fetch, browser (Playwright)
│ ├── storage/ ← artifact store: S3, local filesystem
│ ├── vector/ ← vector DB abstraction
│ ├── contract/ ← Tool interface, CallResult, registry
│ ├── auth/ ← provider auth abstraction, OAuth device flow
│ ├── workspace/ ← sandbox path resolution, workspace layout
│ ├── monitoring/ ← Prometheus metrics, OTel spans
│ ├── docling/ ← PDF/DOCX/audio conversion via docling-serve
│ ├── grpc/ ← proto definitions and generated code
│ └── config/ ← app-level config from env
└── internal/ ← private implementation (do not import directly)
seshat-ai and any third-party consumer must import
pkg/*only, neverinternal/*.
| Provider ID | Service | Auth |
|---|---|---|
anthropic |
Anthropic | ANTHROPIC_API_KEY |
openai |
OpenAI | OPENAI_API_KEY |
gemini |
Google Gemini | GOOGLE_API_KEY |
mistral |
Mistral AI | MISTRAL_API_KEY |
deepseek |
DeepSeek | DEEPSEEK_API_KEY |
ollama |
Ollama (local) | none |
openrouter |
OpenRouter | OPENROUTER_API_KEY |
bedrock |
AWS Bedrock | AWS_ACCESS_KEY_ID + region |
vertex |
GCP Vertex AI | ANTHROPIC_VERTEX_PROJECT_ID + region |
foundry |
Azure AI Foundry | ANTHROPIC_FOUNDRY_API_KEY |
codex |
ChatGPT Pro (OAuth) | device-code flow |
minimax |
MiniMax | MINIMAX_API_KEY |
z-ai |
Z.ai | Z_AI_API_KEY |
opencode |
OpenCode Zen | OPENCODE_API_KEY |
workers-ai |
Cloudflare Workers AI | CLOUDFLARE_API_KEY |
Full model listings and capabilities: docs/providers.md.
# 1. Install
curl -fsSL https://raw.githubusercontent.com/EngineerProjects/seshat/main/scripts/install.sh | bash
# Reload your shell (or open a new terminal) if prompted, then:
# 2. Configure your provider
seshat config --provider anthropic --api-key sk-ant-...
seshat config --model anthropic:claude-sonnet-4-20250514
# 3. Start chatting
seshat chat # new session (opens TUI)
seshat chat --continue # resume last session
seshat chat --resume <session-id> # resume a specific session
seshat run "list all TODO comments in this codebase" # one-shot taskNo API key? Use Ollama for free local inference:
seshat config --provider ollama --model ollama:llama3.2(requires Ollama running locally)
Developers building from source: see the Development section below.
Skills are Markdown files that encode expertise injected into the agent's system prompt at runtime.
.seshat/skills/
go-conventions.md # "always use context.Context as the first parameter..."
git-workflow.md # "never commit to main, always open a PR, squash before merge..."
security-rules.md # "never log secrets, validate all external input at boundaries..."
The official skill collection is seshat-skills, installable from any URL directly from the CLI.
Any MCP server is immediately usable — no additional development needed.
client, _ := sdk.NewClient(&sdk.ClientConfig{
MCPServers: []sdk.MCPServerConfig{
{Name: "github", Command: "npx", Args: []string{"-y", "@modelcontextprotocol/server-github"}},
{Name: "postgres", Command: "npx", Args: []string{"-y", "@modelcontextprotocol/server-postgres", "postgresql://..."}},
{Name: "slack", Command: "npx", Args: []string{"-y", "@modelcontextprotocol/server-slack"}},
},
})Full architecture diagrams (Mermaid): docs/vision/diagrams.md.
| Doc | What it covers |
|---|---|
| Vision & Roadmap | Project idea, design principles, Level 1->2->3 roadmap |
| Architecture | System design, layer diagrams, query loop state machine |
| SDK Guide | ClientConfig, sessions, streaming, callbacks, MCP |
| Tools | Built-in tools reference, permission pipeline |
| Providers | Multi-provider routing, retry, circuit breaker |
| Prompt System | Section assembly, stage overlays, cache control |
| Skills | Skills system, loading order, injection |
| Transports & Setup | gRPC setup, proto codegen, env vars |
| Multi-Agent Teams | Agent profiles, mailbox, dispatcher, TeamBus |
# Linux / macOS — installs all dependencies, builds, wires git hooks
git clone https://github.com/EngineerProjects/seshat
cd seshat
make setup
# Windows (PowerShell — make is not available by default on Windows)
powershell -ExecutionPolicy Bypass -File scripts\setup.ps1make setup handles everything: Go version check, ripgrep, uv, Python venv with docling-serve, and the final build. Binaries land in bin/.
make build # build CLI and gRPC binaries to bin/
make test # run all tests
make test-race # run tests with race detector
make lint # golangci-lint
make fmt # gofmt
make hooks # (re-)install git pre-commit hooks
make install-python # install/update the Python venv + docling-serve only
make start-docling # start docling-serve manually (auto-started by seshat chat)
make clean # remove bin/
make clean-runtime # erase runtime data (~/.config/seshat-cli)
make clean-all # bothWhen the CLI is installed via curl | bash or go install, use the built-in setup command to manage the Python environment:
seshat setup # install uv + docling-serve
seshat setup --check # show status without installing
seshat setup --python 3.12 # use a specific Python version
seshat setup --extras gpu # GPU-accelerated doclingSeshat stores sessions, config, and the Python venv under a platform-appropriate directory:
| OS | Default path |
|---|---|
| Linux | ~/.config/seshat-cli/ (respects $XDG_CONFIG_HOME) |
| macOS | ~/.config/seshat-cli/ |
| Windows | %APPDATA%\seshat-cli\ |
Override with SESHAT_RUNTIME_ROOT=/your/path seshat chat.
ripgrep — the
globandgreptools requireripgrep(rg). Included inmake setup; install separately withmake install-deps.
docling-serve (optional) — enables the
read_document_urltool for PDF/DOCX conversion. Included inmake setupviauv(no system Python required). Seshat auto-starts it on launch when installed.
Linux — primary development and testing platform. Fully supported.
macOS — code is written to support macOS and basic testing has been done, but macOS support is not yet fully validated. If you hit an issue, please open a report.
Windows — PowerShell setup script included and paths are handled (
%APPDATA%), but Windows support has not been tested yet. Contributions and test reports welcome.
See CONTRIBUTING.md for the full contribution guide.
To report a vulnerability, see SECURITY.md.







