* feat: render rich media embeds for MCP tool results Detect structured media JSON (stream_url, results, sessions) in MCP tool output and render interactive cards instead of plain text. Web UI: media cards with thumbnail, title, metadata, and click-to-play video/audio. HLS via lazy-loaded hls.js with direct-stream preference. Collapsed raw JSON (API keys redacted) for inspection. Discord: rich embeds with proxied thumbnail images (fetched by the bot since Discord CDN cannot reach private media servers). Search results as numbered lists, session state as "Now Playing" cards. Stream URLs never exposed in embeds — web_url used for safe clickable links. CI: vendor hls.js 1.6.15 with renovate tracking and update script. * fix: address PR #292 review — SSRF guards, streaming fetch, tests - URL validation: reject non-http(s) schemes and userinfo in thumbnail URLs. Private IPs intentionally allowed (media servers are on LAN). - Streaming fetch: use http.stream() with aiter_bytes() and a running byte count to enforce the 2MB cap without buffering the full response. Validate content-type is image/* before downloading. - Resilience: wrap try_build_media_embed in try/except in bot.py so a media embed failure falls through to the code-block path. - LICENSE: download hls.js LICENSE from npm on update instead of only copying from old dir. - Tests: add 19 new tests — try_parse_media (8 cases), _is_safe_image_url (7 cases), embed builders (4 cases including stream_url exclusion and string season/episode safety). * chore: add LICENSE file for vendored hls.js * fix: remove ANSI escape codes from tool preview fields Preview text (tool args, URLs, queries) was wrapped in DIM/RESET ANSI codes at the source in session.py, which leaked into SSE events and rendered as raw escape sequences in Discord and the web UI. Move ANSI styling to the CLI consumer (cli.py) where it belongs. Also escape markdown in Discord tool name titles to prevent __ from being interpreted as underline formatting. * fix: drop [MCP: server] prefix from tool descriptions The prefix made MCP tools look second-class compared to builtins, causing models to hesitate using them. The server name is already encoded in the tool name (mcp__server__tool). * feat: pretty-print JSON tool output, player error state, broader key redaction - JSON tool results are detected and pretty-printed with 2-space indent instead of rendering as a wall of text - API key redaction extended to cover api_key, apiKey, api-key, and token query params across all tool output (not just media embeds) - Video/audio player shows styled error message when stream fails to load instead of leaving a broken player element - Both appendToolOutput and replayHistory use shared renderToolOutput() * fix: designer review — player error retry, contrast, tool-cmd cap - Player error: role="alert" for screen readers, retry button that reuses existing play handler, includes media title in error message - Light theme: darken --red from #dc2626 to #b91c1c (5.7:1 contrast on --code-bg, was 4.3:1 failing WCAG AA at 12px) - Pretty-print collapsed raw JSON in media embeds (was missed earlier) - Cap .tool-cmd at 120px to prevent tools with many args from making approval blocks disproportionately tall in history replay - Dedicated .media-player-error class instead of reusing .tool-output * fix: Discord tool info name matching regression, suppress deprecation warning The escape_markdown call on tool names was stored for matching against ToolResultEvent.name, but event.name is raw/unescaped. The escaped name never matched, so the "Running → Done" transition silently failed and previews disappeared from the status embed. Fix: store raw name for matching, use escaped name only for display. Also suppress discord.py's re.sub count deprecation warning (Python 3.13+ issue, fixed upstream). * fix: update MCP tool description tests to match prefix removal * fix: address PR #292 review round 2 - Retry button: handle missing span children in click handler so retry buttons from player error state don't throw - Footer count: use len(lines) instead of min(len(results), 10) to reflect actual rendered count after char budget truncation - Null display: use "null" instead of "None" in JS tool arg preview - Broader redaction: also redact JSON "api_key": "..." patterns - SSRF hardening: block loopback and link-local IPs plus cloud metadata hostnames in thumbnail fetch (private LAN IPs still allowed)
Turnstone
Multi-node AI orchestration platform. Deploy tool-using AI agents across a cluster of servers with direct HTTP routing, interactive interfaces, and enterprise governance.
Named after the Ruddy Turnstone (Arenaria interpres) — a shorebird that flips stones to discover what's hiding underneath.
Release Tracks
| Track | Install | Docker | Description |
|---|---|---|---|
| Stable | pip install turnstone |
ghcr.io/turnstonelabs/turnstone:stable |
Production-grade. Bugfixes only. |
| Experimental | pip install turnstone --pre |
ghcr.io/turnstonelabs/turnstone:experimental |
New features. May have rough edges. |
See docs/releasing.md for the full release process.
What it does
Turnstone gives LLMs tools — shell, files, search, web, planning — and orchestrates multi-turn conversations where the model investigates, acts, and reports.
- Interactive sessions — terminal CLI or browser UI with parallel workstreams
- Cluster dashboard — real-time view of all nodes and workstreams with console routing proxy
- Intent validation — LLM judge evaluates every tool call with risk assessments and evidence
- Governance — RBAC, OIDC SSO, tool policies, skills, usage tracking, audit logs
- Multi-provider — OpenAI-compatible APIs (vLLM, llama.cpp, NIM) and Anthropic Messages API
- MCP support — external tool servers with native deferred loading (Anthropic/OpenAI) or BM25 fallback
Quickstart
pip install turnstone
# Terminal REPL
turnstone --base-url http://localhost:8000/v1
# Browser UI
turnstone-server --port 8080 --base-url http://localhost:8000/v1
# Cluster dashboard
pip install turnstone[console]
turnstone-console --port 8090
Docker
cp .env.example .env # edit LLM_BASE_URL, OPENAI_API_KEY, etc.
docker compose --profile production up
See QUICKSTART.md for the bootstrap wizard and docs/docker.md for Docker configuration and profiles.
Programmatic (SDK)
from turnstone.sdk import TurnstoneServer
with TurnstoneServer("http://localhost:8080", token="tok_xxx") as client:
ws = client.create_workstream(name="demo")
result = client.send_and_wait("Analyze the error logs", ws.ws_id, auto_approve=True)
print(result.content)
Tools
Built-in tools for shell, files, search, web, memory, notifications, and autonomous sub-agents — plus external tools via MCP with native deferred loading. See docs/tools.md for the full reference and docs/mcp.md for MCP configuration.
Architecture
Single-node: Client → Server (direct HTTP + SSE). No external dependencies beyond the database.
Multi-node: Client → Console (hash ring routing proxy) → Server nodes. The console maintains a 65536-entry bucket cache for O(1) workstream routing. A rebalancer daemon redistributes buckets when nodes join or leave.
| Component | Purpose |
|---|---|
turnstone |
Terminal CLI (REPL) |
turnstone-server |
Web UI + REST API + SSE events |
turnstone-console |
Cluster dashboard + routing proxy + admin panel |
turnstone-channel |
Channel gateway (Discord, with adapters for Slack/Teams planned) |
turnstone-admin |
User/token management CLI |
turnstone-eval |
Eval harness for prompt/tool optimization |
turnstone-bootstrap |
LLM-guided setup wizard |
Diagrams
UML diagrams in docs/diagrams/:
| Diagram | Description |
|---|---|
| System Context | Components and external dependencies |
| Package Structure | Python modules and dependency graph |
| Core Engine | SessionUI, ChatSession, LLMProvider |
| Conversation Turn | Message lifecycle through the engine |
| Tool Pipeline | Prepare / approve / execute |
| Workstream States | State machine transitions |
| Console Data Flow | Dashboard data collection |
| Deployment | Docker Compose topology |
| Auth | JWT, scopes, login flows |
| Channels | Discord adapter + routing |
| Judge | Intent validation pipeline |
| OIDC | SSO authorization code flow |
Documentation
| Topic | Link |
|---|---|
| Configuration reference | docs/settings.md |
| API reference | docs/api-reference.md |
| Docker deployment | docs/docker.md |
| Intent validation (judge) | docs/judge.md |
| Governance & RBAC | docs/governance.md |
| OIDC SSO | docs/oidc.md |
| TLS / mTLS | docs/tls.md |
| Channel integrations | docs/channels.md |
| Console dashboard | docs/console.md |
| Eval harness | docs/eval.md |
| Tools reference | docs/tools.md |
| MCP integration | docs/mcp.md |
Requirements
- Python 3.11+
- An OpenAI-compatible API endpoint or Anthropic API key
- Optional: PostgreSQL (
pip install turnstone[postgres]), Anthropic (pip install turnstone[anthropic]) - Git LFS for cloning (diagram PNGs)
License
Business Source License 1.1 — free for all use except hosting as a managed service. Converts to Apache 2.0 on 2030-03-01.
