synapse-layer

MCP-native infrastructure for persistent AI agent memory with encrypted storage, semantic retrieval and cross-agent continuity

A new way for AI to search for data
View on GitHub
13GitHub stars

Python

What XERJ indexed

Snapshot

Whole repository

The whole repository at commit b6c63d3120 (2026-10-22).

Selected work

“align public claims with the real cryptography (G7)”. 4 files, 204 lines in synapse_memory, tests, examples.

Licence

The repository

Apache-2.0

Checked by a person at the pinned commit.

The XERJ corpus

Apache-2.0, with credit

The author agreed by email on 2026-10-22. Same terms as the repository. Answers name the repo, the commit and the file:line.

in licence reviewnot in the hub yetsuggested use: adapt with attribution

ai-agentsencrypted-memorymcpmemorycross-agent-memorypersistent-memorytrust-quotientagent-infrastructure

Example questions

The prompt

Paste it into your AI agent. It clones SynapseLayer/synapse-layer at the pinned commit and indexes it on your machine.

Search the GitHub repository SynapseLayer/synapse-layer with XERJ (https://hub.xerj.org/corpus/synapselayer--synapse-layer).
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/SynapseLayer/synapse-layer synapse-layer && git -C synapse-layer checkout b6c63d3120136cd8284a665f4846e0372538ad6e
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./synapse-layer --url http://127.0.0.1:9200 --prefix synapse-layer --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

Selected work and consent: the XERJ registry.