agent-fact-system
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Alternatives to agent-fact-system
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- AlicenseNot gradedqualityBmaintenanceEnables coding agents and other MCP clients to read and write the same durable facts in a local SQLite memory, searched by embedding plus full text and separated into global and per-repository scopes, with a browser notebook and ZIP backup/migration. Runs over stdio or HTTP, keeping search on-machine and secrets redacted before storage.MIT
- AlicenseAqualityAmaintenanceMCP server exposing a deterministic, local knowledge graph over stdio. Zero LLM calls in the bridge; answers are classified as Fact, Inference, or Unknown and persisted in redb (ACID, BLAKE3-hashed).1015Apache 2.0
- AlicenseNot gradedqualityCmaintenanceEnables coding agents to keep a local knowledge graph across sessions and checkpoints, restoring project context after tabs or model changes, and to ground every answer with an explicit verdict from the graph. Runs entirely on the user's machine over MCP/stdio or local JSON-RPC with no third-party runtime dependencies.13Apache 2.0
- AlicenseNot gradedqualityCmaintenanceA local-first compiled knowledge graph MCP server that provides structured memory for AI agents with full-text search, vector embeddings, and timeline tracking.639 npm8MIT
- AlicenseNot gradedqualityAmaintenanceA local-first MCP server that lets coding agents record what they learn as provenance-carrying observations, retrieve and traverse that shared project memory, and keep contradictory claims side by side for human mediation. It enables opt-in peer sync of a workspace across machines, with every assertion keeping its source, basis, and computed trust tier.Apache 2.0
- AlicenseNot gradedqualityAmaintenanceProvides local-first persistent memory with a typed knowledge graph and bounded multi-hop retrieval via MCP, letting coding agents and local LLM systems store, search, and recall facts across sessions without hosted services or model dependencies.MIT
TDQS
Scored across 14 tools
Each tool targets a distinct resource/action: fact_get, fact_search, and fact_propose cover fact reading and proposing; timeline, health, and stats are separate system views; the eight document_* tools each perform a unique operation on documents. There is only a very minor overlap between health and stats, but their descriptions clearly differentiate them.
The fact_* and document_* tools use a prefix-plus-verb pattern (fact_get, document_put), but timeline, health, stats are bare nouns, and document_tags, document_links, and document_backlinks are noun-noun constructions. The mixed conventions are readable but not consistent enough for a high score.
Fourteen tools is within the well-scoped range for a system that manages facts and optional document capabilities. Each tool has a clear purpose, and the count is reasonable for the domain.
The fact lifecycle covers get, search, and propose, which is appropriate for a canonical/adjudicated system. Document tools cover get, list, search, put, resolve, tags, links, and backlinks, but there is no explicit delete operation for documents or facts, which is a minor gap.