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PopNx MCPMCP servers for people who use AI · explained in plain words

Data Olympus

by knaisomaversion 0.11.4i★ –iRuns on your computer
Registry nameio.github.knaisoma/data-olympus

Install

Overview

Description from the maker (original English)

Governance-grade knowledge-base format (OKF-compatible) plus CLI and single-writer MCP server

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: Streamable HTTP
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: KB_MAIN_PATH, KB_INDEX_PATH, KB_HTTP_PORT

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "data-olympus": {
      "command": "uvx",
      "args": [
        "data-olympus"
      ],
      "env": {
        "KB_MAIN_PATH": "your-value",
        "KB_INDEX_PATH": "your-value",
        "KB_HTTP_PORT": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add data-olympus --env KB_MAIN_PATH=your-value --env KB_INDEX_PATH=your-value --env KB_HTTP_PORT=your-value -- uvx data-olympus

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "data-olympus": {
      "command": "uvx",
      "args": [
        "data-olympus"
      ],
      "env": {
        "KB_MAIN_PATH": "your-value",
        "KB_INDEX_PATH": "your-value",
        "KB_HTTP_PORT": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "data-olympus": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "data-olympus"
      ],
      "env": {
        "KB_MAIN_PATH": "your-value",
        "KB_INDEX_PATH": "your-value",
        "KB_HTTP_PORT": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • KB_MAIN_PATH env
    Path to the git-backed knowledge bundle this server indexes and serves.
  • KB_INDEX_PATH env
    Path to the generated SQLite index. Rebuilt atomically and swapped in.
  • KB_HTTP_PORT env
    Port the streamable HTTP MCP server listens on. Defaults to 8080.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account knaisoma, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7271 servers in this category
  • Published to the registry more recently than 74% of the other 7271 servers in this category
  • Basic checks equal to or better than 100% of the other 7271 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Data Olympus safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.11.4) reached the registry 12 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

data-olympus

New here? Start with [WHY.md](WHY.md). It is the story behind the project: the problem we kept hitting with coding agents, what data-olympus does differently, how it relates to Google's Open Knowledge Format, and where our benchmarks say it is strong and where it is not. The rest of this README is the technical reference.

data-olympus is a governance-grade knowledge-base format and server for agent workforces. It is readable by Open Knowledge Format (OKF) v0.2 consumers: it inherits OKF's directory structure, frontmatter conventions, reserved filenames, and link model, then layers governance extensions on top (stable id, controlled type/status/tier fields, supersedes chains) plus a single-writer MCP server and a CLI. CI proves two concrete directions against official Google OKF v0.2 commit ad30107c31c06aec8a7d5636e0d1058118604e6f: its reference visualization consumer reads every concept in example-bundle, and data-olympus imports, lints, indexes, searches, and retrieves the pinned official Bitcoin sample. This is fixture-scoped interoperability evidence, not a blanket guarantee for every OKF bundle or future upstream revision. The result is a git-native, version-controlled document graph of engineering standards, architectural decisions, and project knowledge that agents and humans can read, search, and extend without any proprietary service.

It governs *decisions*, not code. When an agent is about to make a choice (a library, a pattern, a migration), data-olympus surfaces the established standard or decision that should govern that choice. It is deliberately not a code-search, reference-finding, or "where is X used" tool: LSP, grep, and Sourcegraph already do that well. The retrieval task it targets is coding-intent to governing-rule, and it helps where current model interaction during vibe-coding is weakest: keeping the model aligned to patterns the team has already established as correct.

Status: pre-1.0 beta. Stable releases are distributed through PyPI and GHCR.

Why

  • Portable, no lock-in. The entire KB is a directory of markdown files in git. No database, no proprietary schema, no vendor.
  • Git-native diffs and review. Every change is a commit. Proposed edits go through a pending queue before commit; history is plain git log.
  • Agent and human readable. Plain markdown with YAML frontmatter. No SDK required to read or author a document.
  • Governed multi-agent writes. The single-writer MCP pipeline (advisory locks, per-session worktrees, durable push queue) prevents concurrent write races without requiring distributed locking infrastructure.
  • Queryable by status, tier, and type. Filter by status: accepted, tier: T1, or type: decision without post-processing. The supersedes chain makes it possible to trace decision history across the graph.
  • Tested with official OKF tooling. CI pins an exact Google OKF revision and proves both consumption directions over committed fixtures. The pin, fixture checksum, and Apache 2.0 license provenance live in tests/okf/reference.json.

Quickstart

Requires Python 3.13+ and uv. Run the stable CLI directly from PyPI:

uvx --from data-olympus data-olympus --help

Install it persistently when you are ready to create a bundle and run the server:

uv tool install data-olympus

data-olympus init my-kb data-olympus-mcp --help

An announced candidate remains opt in through its exact PyPI version. Replace X.Y.ZrcN with the candidate named on the releases page, if any:

uvx --from 'data-olympus==X.Y.ZrcN' data-olympus --help

See release channels for what each channel means, how to verify a candidate before adopting it, and how to roll back.

See docs/quickstart.md for bundle initialization, server startup, readiness, agent registration, and the contributor source installation.

See docs/adoption.md for the full bundle authoring guide.

Documentation

  • SPEC.md: format specification (bundle layout, frontmatter schema, serving contracts).
  • docs/quickstart.md: verified local-run procedure.
  • docs/adoption.md: bring-your-own-KB guide (author, lint, index, serve, wire an agent).
  • docs/serving.md: single-replica serving model, read-only replicas, git pull loop, health/readiness/liveness split, proxy headers, audit-log rotation.
  • docs/operations.md: production runbook: backup, upgrade, recovery playbooks (degraded/fetch-failed, history rewrite, frozen/demoted push entries, orphaned locks), the health/alerting model, and release channels (stable and candidate, verification, rollback).
  • docs/comparison.md: how data-olympus relates to OKF, enterprise catalogs, markdown KB tools, agent-context conventions, RAG, and ADR tooling.
  • docs/okf-profile.md: field-by-field OKF profile: which governance extensions are stable, which are runtime-only serving fields, and which are experimental candidates.
  • docs/glama.md: Glama registry claim, release, and score-maintenance notes.
  • docs/mcp-registry.md: official MCP Registry notes, what server.json declares, and the checklist for publishing.
  • docs/enforcement.md: turning the KB into a mandatory consultation gate (hooks, kb enforce).
  • benchmarks/README.md: retrieval benchmark methodology and how to reproduce the numbers in docs/comparison.md.
  • SECURITY.md: supported versions and how to report a vulnerability.

License

Apache 2.0. See LICENSE and NOTICE.

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