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consolidation-memory
charliee1w February 24, 2026
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Local-first persistent memory for AI agents — store, recall, and consolidate knowledge across sessions using FAISS, SQLite, and any LLM. MCP server for coding agents and any MCP client.
Agent Definition
# consolidation-memory [](https://pypi.org/project/consolidation-memory/) [](https://github.com/charliee1w/consolidation-memory/releases) [](https://github.com/charliee1w/consolidation-memory/actions) [](https://pypi.org/project/consolidation-memory/) [](LICENSE) [](https://github.com/charliee1w/consolidation-memory/stargazers) Trust-calibrated working memory for coding agents. `consolidation-memory` is built around a simple stance: claims are the reusable unit, episodes are the raw evidence, and code drift is a first-class reason to distrust stale memory. The system stores episodic events, consolidates them into structured knowledge and claims, and serves the same trust-aware retrieval semantics across Python, MCP, REST, and OpenAI-style tool calls. ## Design Philosophy - Treat the system as a trust layer for coding-agent memory, not a generic blob store. - Prefer reusable claims with provenance over raw episodic recall. - Keep uncertainty visible through temporal validity, contradiction history, and drift challenge signals. - Preserve local-first inspectability: SQLite, FAISS, markdown, and logs should all stay understandable on disk. - Support shared memory only when scopes and policy make reuse safe. ## What It Is And Is Not `consolidation-memory` is for: - coding agents that need durable, inspectable working memory - teams that want reusable claims without mixing unrelated contexts - workflows where code changes should automatically reduce trust in older conclusions `con
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