Synaptra
PulseGate's liveness check found it on 14 Sep 2026; it is registered on GitHub and PyPI and has been in the index since 1 Aug 2026. How this is checked
Synaptra is an open-source Python package that implements biologically-inspired memory for AI agents. It functions as an MCP (Model Context Protocol) server supporting mechanisms such as memory decay, consolidation, and multiple retrieval strategies. Designed for developers building autonomous agents, it provides a lightweight, installable library that can be self-hosted to give agents more human-like long-term memory capabilities.
Inferred · not functionally tested
Overview
5 featuresPurpose: Implementing realistic, biologically-plausible memory systems for AI agents that support forgetting, memory consolidation, and context-aware retrieval.
Inferred · not functionally tested
Audience: AI developers
Inferred · not functionally tested
Functions: agents
Inferred · not functionally tested
Interfaces: API: indicated (inferred, not tested) · MCP: indicated (inferred, not tested) · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)
Recorded constraints: pricing: open_source · license: MIT · platforms: CLI · deployment: cli, api_only, self_hosted
Constraint provenance is unknown; confirm requirements with the publisher.
Record sources: pypi.org · github.com. These links do not verify the individual claims.
Synaptra sits in PulseGate's Memory & skills category. Inferred · not functionally tested: It focuses on implementing realistic, biologically-plausible memory systems for AI agents that support forgetting, memory consolidation, and context-aware retrieval. Inferred · not functionally tested: Synaptra is an open-source project aimed at AI developers. Basis unknown · not verified: The project is open source (MIT). Basis unknown · not verified: It ships for the command line and API, and it can be self-hosted.
Kaushik Hazra builds and maintains Synaptra, and it first shipped in 2026. Development happens publicly on GitHub with 3 commits in the last 90 days. Inferred · not functionally tested: Key capabilities include Memory Decay, Memory Consolidation, and Multi-strategy Retrieval. Inferred · not functionally tested: Catalogued interfaces include an MCP server.
Summary written by a language model from the project’s public pages.
Tasks: Inferred · not functionally tested
- Memory Decay
- Memory Consolidation
- Multi-strategy Retrieval
- MCP Server
- Biological Modeling
Topics: Inferred · not functionally tested
Built with & integrations
Trust & compliance
Indexing history
3What PulseGate has recorded for this listing
Frequently asked questions about Synaptra
- What is Synaptra?
- Inferred · not functionally tested: Synaptra focuses on implementing realistic, biologically-plausible memory systems for AI agents that support forgetting, memory consolidation, and context-aware retrieval. It is catalogued under Memory & skills on PulseGate.
- Who is Synaptra for?
- Inferred · not functionally tested: Synaptra is an open-source project built for AI developers.
- Is Synaptra free?
- Basis unknown · not verified: Yes — Synaptra is open source under the MIT license and free to use.
- What platforms does Synaptra run on?
- Basis unknown · not verified: Synaptra runs on the command line and API. It can also be self-hosted.
- Is Synaptra still active?
- PulseGate's liveness check found it on 14 Sep 2026. Its GitHub repository shows 3 commits in the last 90 days.
- Who develops Synaptra?
- Synaptra is developed by Kaushik Hazra.
- When did Synaptra launch?
- Synaptra first shipped in 2026.
- Is Synaptra open source?
- Basis unknown · not verified: Yes — Synaptra is open source under the MIT license, developed on GitHub.
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