contextweave
Long-term memory infrastructure for AI agents
What XERJ indexed
Snapshot
The whole repository at commit 8951dd9ca6 (2026-10-27). main is 22 commits ahead.
Selected work
“Split runtime and admin MCP surfaces”. 7 files, 315 lines in server, scripts, deploy.
Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
The author agreed by email on 2026-10-28. Same terms as the repository. Answers name the repo, the commit and the file:line.
selected for the XERJ Corpus Hublicence clearedsuggested use: adapt with attribution
agent-memoryagent-memory-mcpagent-memory-systemai-agentsai-memorycontext-managementlong-term-memoryretrieval
Example questions
- How does contextweave implement agent-memory?
- Where does contextweave handle “Split runtime and admin MCP surfaces”?
- What does server do in contextweave?
Inside the indexed corpus
- 285 files, 3.6 MB in total, about 12.9 KB per file.
- The selected commit changed 7 of those files (2.5%).
- Languages by size: JavaScript 94.6%, Python 3%, TypeScript 1.8%, Shell 0.6%, Dockerfile 0.1%.
- On GitHub since 2026-10-25, last push 2026-10-31, 29 commits on main.
- The pin is 22 commits behind main; the corpus answers from the pinned code, not the newest.
Licence on GitHub and in the corpus
GitHub reported Apache-2.0 for Lucien-rose/contextweave on 2026-10-31, and the LICENSE file at commit 8951dd9ca6 was reviewed as Apache-2.0. They match, so answers from this corpus carry the same terms as the live repository.
Contributors
Phina (@Lucien-rose) has 1 selected repository on the hub.
Using XERJ with contextweave
- What is agentic memory? A plain answer contextweave is tagged agent-memory on GitHub.
- XERJ vs Mem0, Zep, Letta and Cognee for agent memory
- RAG without a vector database: one hybrid index The hub files it under AI, prompts and agents.
- Ask questions about a GitHub repo without cloning it
The prompt
Paste it into your AI agent. It clones Lucien-rose/contextweave at the pinned commit and indexes it on your machine.
Search the GitHub repository Lucien-rose/contextweave with XERJ (https://hub.xerj.org/corpus/lucien-rose--contextweave). Run these in a shell, in order, and check each result before the next: 1. xerj --help (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh 2. git clone https://github.com/Lucien-rose/contextweave contextweave && git -C contextweave checkout 8951dd9ca6f0a5947f47503c39f6be92696db909 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./contextweave --url http://127.0.0.1:9200 --prefix contextweave --progress plain 5. xerj autoindex map --url http://127.0.0.1:9200 Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt Licence: Apache-2.0. Keep the copyright notice and credit the authors.
Related
PhinaAI, prompts and agents corporadunorth595--ai-agent-memoryxobotyi--cc-foundry-infrastructureflagembeddingdreamforgestudiollc/EMETvvooki-sys/loomemmemoweft/memoweft
Stats: GitHub API, fetched 2026-10-31. Snapshot: the git tree at the pinned commit. Selected work and consent: the XERJ registry.