head to head · open source
cognee vs mcp-server-elasticsearch
cognee has 30,848 GitHub stars, 3,066 forks, 495 open issues and last shipped yesterday. mcp-server-elasticsearch has 718 stars, 155 forks, 23 open issues and last shipped yesterday. cognee leads on adoption by 4,196% (30,848 vs 718 stars). cognee is written in Python under Apache-2.0; mcp-server-elasticsearch is written in Rust under Apache-2.0. cognee has attracted 10% as many forks as stars, mcp-server-elasticsearch 22%. mcp-server-elasticsearch was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| cognee | mcp-server-elasticsearch | |
|---|---|---|
| GitHub stars | ★ 31K | ★ 718 |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Rust |
| Last push | 2026-09-19 | 2026-09-19 |
| Forks | ⑂ 3.1K | ⑂ 155 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick cognee if
- You weight community size — 31K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick mcp-server-elasticsearch if
- You want the mcp-server-elasticsearch feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and mcp-server-elasticsearch fits your workflow better
About cognee
Cognee is an open source AI memory platform for agents, released under the Apache 2.0 license and written in Python. It ingests data in any format and builds a self hosted knowledge graph that agents query to recall, connect, and act with full context across sessions. The project lives in the Python ecosystem, installs through standard package managers, and sits in the AI and machine learning infrastructure category alongside graph databases and context engineering tooling. A companion research paper, "Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning" by Markovic et al., 2025, docu…
read the full cognee overview →
About mcp-server-elasticsearch
Connects AI agents to Elasticsearch data over Model Context Protocol so agents can query, analyze, and retrieve from indices in natural language without custom APIs — built for teams running Elasticsearch 8.x or 9.x that want MCP compatible clients such as Claude Desktop, Cursor, or VS Code to read their indices, though it is now deprecated in favour of the Elastic Agent Builder MCP endpoint.
read the full mcp-server-elasticsearch overview →
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Frequently asked questions
Is cognee or mcp-server-elasticsearch more popular?
cognee has 30,848 GitHub stars and mcp-server-elasticsearch has 718. cognee has the larger community by that measure.
Are cognee and mcp-server-elasticsearch free?
Both are open source. cognee is licensed under Apache-2.0 and mcp-server-elasticsearch under Apache-2.0. Neither carries a licence fee.
What is the difference between cognee and mcp-server-elasticsearch?
cognee is written in Python and mcp-server-elasticsearch in Rust. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, cognee or mcp-server-elasticsearch?
Choose cognee if you want the larger community (30,848 stars) or its Apache-2.0 licence terms. Choose mcp-server-elasticsearch if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.