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Memory and knowledge · MCP server

Data Olympus: MCP server, setup and security

Data Olympus is an open-source MCP server that lets an AI agent retrieve coding guidance according to its acceptance status and validity. Its repository has 30 stars and its last commit is from October 24, 2026 and it is licensed under Apache-2.0.

Actively maintained

What Data Olympus does

According to its repository: “Git-native Markdown knowledge base for coding agents with proposed vs. accepted guidance, validity windows, supersession chains and status-aware retrieval.”

An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Data Olympus is listed under Memory and knowledge, a category of 250 servers in the directory, where it ranks #125 by stars.

Topics declared by the repository: ai-agents, knowledge-base, knowledge-management, markdown, okf.

Installing and connecting Data Olympus

Distribution modes declared in the official MCP registry:

  • PyPI package (Python, started with uvx or pip)

Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: Python. Listed systems: macOS, Windows, Linux.

Security: what to check

An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Data Olympus. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on June 24, 2026, the knaisoma/data-olympus repository has 30 stars and 7 forks, with 37 open issues. It has more stars than 45% of the servers in the directory. It received changes this month. Version published in the registry: 0.11.3 (October 20, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

Context7Context7 : 63.6K63.6KHindsightHindsight : 53.4K53.4KCogneeCognee : 32.7K32.7KSkill SeekersSkill Seekers : 15.2K15.2KHonchoHoncho : 7.8K7.8KBasic memoryBasic memory : 4.3K4.3KNoteDiscoveryNoteDiscovery : 2.8K2.8KMemantoMemanto : 2.3K2.3KData OlympusData Olympus : 3030
GitHub stars of the most followed servers in the category (log scale); Data Olympus in orange. Checked October 25, 2026.

Verdict

Data Olympus is a reasonable choice; check the points below before connecting it.

Strengths

  • Active project: recent commit
  • Listed in the official MCP registry
  • Permissive licence (Apache-2.0)

Frequently asked questions

How do I install Data Olympus?

Data Olympus is distributed as PyPI package (Python, started with uvx or pip). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of knaisoma/data-olympus.

Is Data Olympus free?

The code is published under the Apache-2.0 licence and can be used free of charge.

Is Data Olympus safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by knaisoma on GitHub. Check who maintains it before giving it access.

What are the alternatives to Data Olympus?

In the same category: Context7, Basic memory, Hindsight, and Cognee. Context7 and Basic memory score higher on our grid.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score