xerj-org/xerj
XERJ is the new way for AI to search data. Its autoindex capability activates agents to know your data without the token waste of grep and sed. One command indexes code, docs, logs and PDFs for search, RAG, security audits and agent memory, using 40x fewer tokens than grep. Elasticsearch compatible, so existing clients just work.
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README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
XERJ: the search engine for AI agents. A new way for AI to search for data: one local Rust binary that indexes your code, docs, specs and logs, plus Corpus Hub packs, and returns cited answers. Local-first search engine and MCP server for AI agents. One Rust binary indexes code, docs, logs, JSONL/CSV and PDFs for BM25 full-text, vector and hybrid search, code search and agent memory, behind an Elasticsearch-compatible API. Works with Claude Code, Cursor and any MCP client. English | 简体中文 | 日本語 | العربية | Español | 한국어 [](https://github.com/xerj-org/xerj/actions/workflows/ci.yml) [](https://github.com/xerj-org/xerj/releases) [](./LICENSE) [](https://github.com/xerj-org/xerj/stargazers) [](https://www.rust-lang.org) [](https://github.com/xerj-org/xerj/discussions) [](https://discord.com/invite/yetXFusXfs) [](https://x.com/xerjorg) [](https://xerj.org/case-studies/reference-coding.html) [](https://xerj.org/docs/cli.html) [](https://xerj.org/docs/queries.html) [](https://xerj.org/docs/recipes/agentic-memory.html) [](https://xerj.org/llms.txt) [](https://xerj.org/llms.txt) [](https://xerj.org/benchmarks) [](https://xerj.org/docs/install.html) [](https://xerj.org/docs/vectors.html) [](https://xerj.org/docs/vectors.html) XERJ is a community-trusted local AI search that indexes any folder automatically, so your coding agent stops burning tokens reading files one by one and pulls the exact code it needs instead. Reference coding is its main use case and the…
Read the full README ↗ · Preview checked 2026-10-30T14:43:54.053Z
Inside the original README — Document outline
- XERJ
- Join the community
- The measured reason: reference coding
- Feed it any folder
- What people point it at
- How the prompt works
- Install by hand
- Index a folder
- Search it
- Score results with Jev
- Connect an agent over MCP
- Supported agents
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Documentation belongs to its respective authors. Reported project/model license: Apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
What this repository does
XERJ is the new way for AI to search data. Its autoindex capability activates agents to know your data without the token waste of grep and sed. One command indexes code, docs, logs and PDFs for search, RAG, security audits and agent memory, using 40x fewer tokens than grep. Elasticsearch compatible, so existing clients just work.
Repository facts
- Owner
- xerj-org
- Primary language
- Rust
- Stars
- 7,357
- Forks
- 382
- Open issues + pull requests
- 34
- License
- Apache-2.0
- Archived
- No
- Default branch
- main
- Created
- 2026-06-30T04:32:45.000Z
- Last push
- 2026-10-15T11:22:42.000Z
Topics and intended use
Owner-supplied topics: ai-search, ai-search-algorithms, ai-search-engine, ai-search-free, ai-search-module, ai-search-optimization, ai-searchengine, bm25-search, elastic-search, elasticsearch, elasticstack, graph-search, graph-semantic-search, hybrid-search, hybrid-semantic-search, search-api, search-engine, semantic-search, vector-database, vector-search
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Source and freshness
Source: GitHub. Metadata observed 2026-10-17T12:07:00.663Z. Daily imports are snapshots, not real-time monitoring.
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