Setoku
Not yet source-checkedOpen-source MCP knowledge server that makes any AI fluent in your company data
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In short
Setoku acts as a governed bridge between AI clients and operational data by mirroring sources into a ClickHouse data lake. It enables natural-language queries and dashboards without SaaS costs, making it best for self-hosted RAG over business data.
Small engineering-led startups already using Claude Code or Claude Desktop who want a self-hosted, MCP-native way to give their AI grounded access to Postgres, GitHub, Slack and finance data without paying a SaaS analytics vendor.
Non-technical teams without ops capacity to run a VPS, enterprises needing SOC2-grade vendor support, or shops standardized on non-MCP AI stacks like bare OpenAI Assistants or Gemini with no client-side MCP layer.
Setoku is an open-source, self-hosted Model Context Protocol (MCP) knowledge server from Hedgy Labs that acts as a governed bridge between AI assistants (Claude Code, Claude Desktop, or any MCP client) and a company's operational data. It runs on a cheap VPS and mirrors PostgreSQL databases, GitHub activity, Vercel/Render deploy logs, Slack messages, and Mercury banking into a unified ClickHouse data lake, then exposes that data through read-only MCP tools plus a maintained layer of metric definitions, entity documentation, and semantic context that improves with use. Because inference happens inside whatever MCP client the user already runs, Setoku never charges for tokens; it is infrastructure, not a model wrapper. Typical workflows include asking Claude to answer ad-hoc analytical questions with live company numbers, generating shareable live-data dashboards from natural-language prompts, letting non-technical employees query governed data without SQL, and giving coding agents grounded context (issues, commits, deploys, incidents) when planning changes. The project ships an opinionated bootstrap script (./deploy/bootstrap.sh) for a fresh Ubuntu box, a Claude Code plugin marketplace entry (/plugin marketplace add Hedgy-Labs/setoku followed by /setoku:onboard), and prompt-driven skills that let an agent scaffold new connectors when a source isn't yet supported. It targets small-to-mid engineering-led teams that want data-sovereign RAG-over-business-data without adopting a closed vendor stack.
Setoku is one of the more coherent takes on 'MCP as a company data plane' I've seen: instead of another closed text-to-SQL SaaS, it's a boring, cheap VPS mirroring your systems into ClickHouse and speaking MCP. If you already live in Claude Code, the /setoku:onboard flow is genuinely slick. It's early, narrow on connectors, and demands sysadmin comfort - but the Apache-2.0 licence and zero inference markup make it a low-risk bet.
— The AI Tool Bible editorial team
Pros
- ✅ Fully open-source under Apache-2.0 with source on GitHub (Hedgy-Labs/setoku), avoiding vendor lock-in
- ✅ Model-agnostic via MCP - works with Claude, Claude Code, or any conforming client
- ✅ Zero server-side inference cost; runs on a $5-12/mo VPS since compute stays in the client
- ✅ Unified ClickHouse data lake ingests Postgres, GitHub, Vercel, Render, Slack and Mercury out of the box
- ✅ Governed, read-only access layer suitable for exposing sensitive data to non-technical staff
- ✅ First-class Claude Code plugin install path (/setoku:onboard) turns setup into a chat flow
- ✅ Ships agent-friendly skills so a coding assistant can wire up missing connectors itself
Cons
- ⚠️ No hosted SaaS - teams must be comfortable running and maintaining a Linux VPS
- ⚠️ Small, young project from Hedgy Labs with limited third-party ecosystem or community track record
- ⚠️ Read-only by design; not a workflow or write-back tool for updating source systems
- ⚠️ Connector list is narrow (six sources); anything outside Postgres/GitHub/Vercel/Render/Slack/Mercury requires DIY
- ⚠️ Value is tightly coupled to Claude/MCP tooling - teams standardized on non-MCP AI stacks get less benefit
- ⚠️ Documentation is early-stage; no published pricing, SLAs, or enterprise support offering
Facts
- API available
- Yes
- Open source
- Yes
- Model used
- Model-agnostic (MCP); commonly paired with Claude / Claude Code
- Hacker News
- 2 stories · top 3 points · last Aug 22, 2026 · checked Oct 20, 2026
- Earliest Wayback capture
- 2026-07-25 (earliest archived capture of the site, not a launch date)
Where this tool sits
Use cases
Frequently asked
- What data sources does Setoku support out of the box?
- Setoku mirrors PostgreSQL databases, GitHub activity, Vercel and Render deploy logs, Slack messages, and Mercury banking into a unified ClickHouse data lake.
- How much does it cost to run Setoku?
- The software is free and open-source under the Apache-2.0 license. The only cost is self-hosting on a VPS, which typically ranges from $5 to $12 per month.
- Which AI clients are compatible with Setoku?
- Setoku is model-agnostic via the Model Context Protocol (MCP) and works with Claude Code, Claude Desktop, or any other conforming MCP client.
- Can Setoku write data back to source systems?
- No, Setoku is read-only by design. It provides a governed access layer for querying data but does not function as a workflow or write-back tool for updating source systems.
- Is Setoku suitable for non-technical teams?
- It is not recommended for non-technical teams without ops capacity, as it requires running and maintaining a Linux VPS. It targets small-to-mid engineering-led teams.