| 08/26 | 7 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
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| 08/26 | 7 |
Zero-dependency CLI memory layer that indexes Claude Code, Codex, and opencode session logs for fast search, agent recall, redaction, stats, and sync.
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| 08/25 | 7 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
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| 08/23 | 7 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
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| 08/23 | 7 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
|
| 08/23 | 7 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
|
| 08/23 | 7 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
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| 08/22 | 7 |
Turns Git-backed Markdown and YAML files into a typed relational graph queried via GraphQL, generated TypeScript, or the Flatbread CLI.
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| 08/22 | 7 |
Zero-dependency CLI memory layer that indexes Claude Code, Codex, and opencode session logs for fast search, agent recall, redaction, stats, and sync.
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| 08/25 | 6 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
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| 08/25 | 6 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/24 | 6 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
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| 08/24 | 6 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/24 | 6 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
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| 08/23 | 6 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
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| 08/20 | 6 |
Persistent, searchable shared memory server for AI coding agents that syncs across clients.
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| 08/19 | 6 |
Zero-dependency CLI memory layer that indexes Claude Code, Codex, and opencode session logs for fast search, agent recall, redaction, stats, and sync.
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| 08/19 | 6 |
Persistent, searchable shared memory server for AI coding agents that syncs across clients.
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| 08/16 | 6 |
Zero-dependency CLI memory layer that indexes Claude Code, Codex, and opencode session logs for fast search, agent recall, redaction, stats, and sync.
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| 08/15 | 6 |
LLM-supervised persistent memory for AI agents with graph-based recall, intent-aware retrieval, importance decay, and automatic deduplication.
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| 08/14 | 6 |
Zero-dependency CLI memory layer that indexes Claude Code, Codex, and opencode session logs for fast search, agent recall, redaction, stats, and sync.
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| 08/14 | 6 |
TypeScript framework combining an agent core with a production harness to run governed, durable domain agents with checkpoints, recovery, and cache reuse.
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| 08/27 | 5 |
Three-line embeddable agent memory layer providing persistent memory and reducing token usage by about 90%.
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| 08/27 | 5 |
Inspectable, portable semantic memory layer for agents and applications, supporting portable capture, groundings, and correction-aware knowledge across SDK, CLI, MCP, adapters, and plugins.
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| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/26 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/25 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/25 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/22 | 5 |
LLM-supervised persistent memory for AI agents with graph-based recall, intent-aware retrieval, importance decay, and automatic deduplication.
|
| 08/21 | 5 |
Local agent-experience loop that learns from AI coding agent sessions, records retro experiments in a typed graph, and proposes repo-specific fixes for review.
|
| 08/19 | 5 |
LLM-supervised persistent memory for AI agents with graph-based recall, intent-aware retrieval, importance decay, and automatic deduplication.
|
| 08/16 | 5 |
LLM-supervised persistent memory for AI agents with graph-based recall, intent-aware retrieval, importance decay, and automatic deduplication.
|
| 08/14 | 4 |
Local-first personal AI with biologically inspired memory, a dream engine, and a P2P skills marketplace.
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