seshat

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SUMMARY

Open-source Go agent runtime for autonomous AI systems and multi-agent automation. MCP, RAG, 15+ LLM providers and 60+ built-in tools in a single binary.

README.md

Seshat

Seshat

Open-source Go agent runtime for governed, multi-provider, self-hostable execution
Built for serious agent work today, with a larger open-source vision behind it.

🌐 Website · 💬 Discussions · 🐛 Issues · 🖥️ seshat-ai


What Seshat Is Today

Seshat is an open-source Go agent runtime for people who need more than a chat shell and less vendor lock-in than a closed assistant.

Its current wedge is concrete:

  • governed multi-turn agent execution
  • tools, files, sandboxed bash, web, browser, MCP, RAG, and skills
  • multi-provider routing with self-hosted and local-first deployment options
  • persistent sessions, permissions, recovery, and audit-friendly behavior
  • CLI/TUI, gRPC, and Go SDK surfaces on the same runtime core

If you want the class of tool people reach for in products like Claude Code, but open, written in Go, multi-provider, and deployable under your own rules, this is the project.

Why This Exists

Most of the market still splits into two weak extremes:

  • chat products that answer well but do not own serious execution
  • low-level frameworks that are flexible but too fragmented, too provider-shaped, or too awkward to ship as a real runtime

Seshat is the missing middle layer: an execution runtime that can actually run agents, call tools, hold sessions, enforce permissions, recover from failures, and stay usable as infrastructure.

The Broader Open-Source Direction

The project still keeps a broader ambition, and that matters for the community.

Seshat is not only about making one strong solo agent. The longer-term direction is organized agentic work: explicit roles, mission memory, structured coordination, durable teams, and an open foundation that others can extend through skills, MCP servers, SDK integrations, and domain-specific workflows.

That larger vision belongs in the docs and in open-source discussion because contributors need the map, not only the current feature list.

Runtime First, Platform Above It

Seshat is the runtime layer.

Use this repository if you want to:

  • run agents locally or self-host them under your own control
  • embed the runtime inside a Go application or internal system
  • extend providers, tools, permissions, MCP integration, or runtime behavior

If you want the full self-hosted platform layer for organizations, use seshat-ai: users, workspaces, REST API, knowledge base, scheduling, governance, and desktop product surfaces built on top of this engine.


🖥️ Terminal UI

seshat chat drops you into a full-featured terminal interface built for long-running agent sessions.

Welcome screen
Welcome — up and running in 10 seconds
Settings panel
Settings panel — every shortcut, one keystroke away (ctrl+p)
Model selection
Model selection — switch across 20+ models in 2 keystrokes
Provider configuration
Provider config — API keys encrypted, scoped per provider
Agent working
Agent at work — full reasoning trace, thinking blocks + tool calls
Agent completing task
Streaming results — streamed responses with markdown + tool timings

Keyboard shortcuts: ctrl+p settings · ctrl+m models · ctrl+s sessions · ctrl+, providers · ctrl+n new session · ctrl+t tasks · ctrl+u copy last response · ctrl+y toggle yolo · ctrl+o open editor · ctrl+g help · ctrl+c quit

Clipboard note (Linux): selection copy works best when wl-clipboard (Wayland) or xclip/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.


🌐 The Seshat Ecosystem

seshat is the headless runtime: pure Go, no UI, no users, no billing. It is the foundation everything else builds on.

🖥️ seshat-ai — Desktop & Platform

→ 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/messages format
  • 📚 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

🤝 Contribution split

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.

📦 Installation

End users — one command, fully configured:

curl -fsSL https://raw.githubusercontent.com/KPO-Tech/seshat/main/scripts/install.sh | bash

Downloads 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 version

Developers — Go toolchain:

# Install the CLI binary
go install github.com/KPO-Tech/seshat/cmd/cli@latest

# Then set up document processing if needed
seshat setup

# Or check what is already installed
seshat setup --check

SDK — embed in your Go application:

go get github.com/KPO-Tech/seshat@latest

🔀 Three Ways to Use It

1. 💻 CLI — seshat

An 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/KPO-Tech/seshat/main/scripts/install.sh | bash

# Developers — binary only via Go toolchain:
go install github.com/KPO-Tech/seshat/cmd/cli@latest
seshat setup          # install uv + docling-serve afterwards if needed
seshat setup --check  # check what is already configured

Configure a provider

seshat config --provider anthropic --api-key sk-ant-...
seshat config --model anthropic:claude-sonnet-4-20250514
seshat config --print

Run

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 reference

Sessions 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.


2. 🌐 gRPC Server

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-grpc

Server 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.proto

One runtime. Every language.


3. 📦 Go SDK

Embed the full runtime in your own Go application.

go get github.com/KPO-Tech/seshat/pkg/sdk
import "github.com/KPO-Tech/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)

📊 How Seshat Compares

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

✨ Capabilities

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)

🗂️ Repository Structure

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, never internal/*.


🌐 Supported Providers

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.


🚀 Quick Start

# 1. Install
curl -fsSL https://raw.githubusercontent.com/KPO-Tech/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 task

No 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

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.


🔌 MCP

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"}},
    },
})

🏗️ Architecture

Seshat Architecture

Full architecture diagrams (Mermaid): docs/vision/diagrams.md.


📖 Documentation

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
Memory and Compaction Session memory, context compaction, memory tool
MCP Client MCP protocol, transports, server configuration
RAG System Chunking, embeddings, hybrid search, document ingestion
Planning Mode Execution modes: execute, plan, pair-programming

🛠️ Development

First-time setup (build from source)

# Linux / macOS — installs all dependencies, builds, wires git hooks
git clone https://github.com/KPO-Tech/seshat
cd seshat
make setup

# Windows (PowerShell — make is not available by default on Windows)
powershell -ExecutionPolicy Bypass -File scripts\setup.ps1

make setup handles everything: Go version check, ripgrep, uv, Python venv with docling-serve, and the final build. Binaries land in bin/.

Daily commands

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       # both

seshat setup (runtime, not source)

When 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 docling

Runtime data directory

Seshat 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.

Runtime dependencies

ripgrep — the glob and grep tools require ripgrep (rg). Included in make setup; install separately with make install-deps.

docling-serve (optional) — enables the read_document_url tool for PDF/DOCX conversion. Included in make setup via uv (no system Python required). Seshat auto-starts it on launch when installed.

OS compatibility

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.


🔒 Security

To report a vulnerability, see SECURITY.md.


📄 License

Apache 2.0

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