Particles
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Alternatives to Particles
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Related Servers
- AlicenseAqualityBmaintenanceEnables AI agents to record, recall, correct, and forget evidence-backed factual claims with temporal history, while explaining whether remembered information is current, historical, or contested.5Apache 2.0
- AlicenseNot gradedqualityAmaintenanceBelief-tracking memory for AI agents. Remember, recall, and ask why: every memory carries evidence, contradictions are surfaced, and retracted facts take their conclusions with them. Zero dependencies, local, MIT.MIT
- AlicenseNot gradedqualityAmaintenanceLocal-first, source-grounded memory for AI agents, with citations, bitemporal history, review-gated corrections, and MCP tools for search and recall.66 PyPI3Apache 2.0
- AlicenseNot gradedqualityCmaintenanceSelf-hosted long-term memory for AI agents on your own Postgres. Facts are dated, versioned and superseded rather than silently overwritten, every recall ships with an inspectable trace, and agents can correct wrong memories from inside the conversation.2Apache 2.0
- AlicenseNot gradedqualityAmaintenanceGives AI agents governed, provenance-tagged memory where facts are invalidated rather than deleted and every recall result carries validity dates, confidence, and replacement links. Stores memory in a local SQLite file with tools for remembering, recalling, invalidating, and pinning facts, plus policy enforcement and an audit trail.406 npm3Apache 2.0
- AlicenseNot gradedqualityAmaintenanceLocal memory for AI agents in one SQLite file on your own machine. Facts carry a validity window and a confidence score, so an outdated one is superseded and downweighted rather than deleted, and retrieval fuses BM25, vector similarity and a knowledge graph.2Business Source 1.1
TDQS
Scored across 16 tools
Most tools target clearly distinct operations: particle listing/show/search, subject listing/search/show, taxonomy listing, corpus listing, lint, quality reporting, event inspection, link suggestions, and graph rendering. The broad `query` tool overlaps somewhat with `particles_list` and `particle_search`, but the descriptions make the lightweight/fingerprint/semantic boundaries reasonably clear. The two link-suggestion tools are similar in naming but operate on different domains, so careful reading is still needed.
The set mixes conventions: core tools mostly use noun_action patterns (`particles_list`, `particle_show`, `subjects_search`), but others use verb_noun (`list_taxonomies`, `list_corpus_entries`) or standalone names (`query`, `lint`, `graph_view`, `quality_report`). Singular/plural usage also varies (`particle_show` vs `subjects_show`, `events_list` vs `event_show`). All names remain readable and snake_case, but the pattern is not fully predictable.
At 16 tools, the surface is slightly above the typical ideal range, but the domain is complex and each tool maps to a fairly distinct read-only inspection, query, reporting, or suggestion capability. The count feels justified rather than bloated, though a few tools could conceivably be consolidated.
The read-only surface covers particles, subjects, taxonomies, corpus entries, events, lint findings, quality reporting, link suggestions, and graph views, which is broad lifecycle coverage for an inspection-oriented MCP server. Minor gaps remain: there is no dedicated tool to show a full corpus entry, and `graph_view`'s manifest scope has no manifest/section discovery tool. These are workable gaps rather than severe dead ends.