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.

Setoku

Open-source MCP knowledge server that makes any AI fluent in your company data

Free· Free / open-source (Apache-2.0). Self-hosting cost only: ~$5-12/mo VPS. No SaaS tier and no per-token inference charges from Setoku itself.RAGModel-agnostic (MCP); commonly paired with Claude / Claude Code

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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.

Best for

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.

Skip if

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.

Editor's take

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

Use cases

MCP knowledge server for Claude CodeRAG over company PostgresNatural-language dashboards on live dataGoverned data access for non-technical staffGrounding coding agents in GitHub and deploy historySlack message search from an AI assistantMercury banking Q&A via ClaudeSelf-hosted alternative to closed analytics copilotsMetric and entity definition layer for LLM analytics

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.