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How it compares

Choose hallouminate when the knowledge should live with a code repository as reviewable markdown. Choose an agent-memory or knowledge-graph system when the primary unit is a user, conversation, agent, or evolving world model instead.

This is a comparison of product shape, not a benchmark. Features change; the links point to upstream documentation and were last checked on 2026-08-01.

If you need… Start with… Why
Architecture decisions, conventions, and gotchas committed with a repository hallouminate The wiki is ordinary markdown under the repo; the search index is derived and local.
A local-first personal or project knowledge base with a richer note schema and knowledge graph Basic Memory Markdown remains central, with observations, relations, project management, and optional cloud sync.
A minimal entity-and-relation memory example for experimenting with MCP @modelcontextprotocol/server-memory A small reference server stores a JSONL knowledge graph without embeddings.
Application-level memory scoped to users, agents, sessions, or runs Mem0 It is a memory layer and SDK/server for applications rather than a repo documentation workflow.
Automatic capture and recall of coding-agent sessions claude-mem It records session activity, compresses it, and recalls relevant context across sessions.
Temporal facts and relationships extracted into a queryable graph Graphiti It models episodes, entities, and time-aware relationships over a graph database.
A code/document graph derived automatically from existing artifacts graphify It parses code, docs, and media into typed nodes and confidence-labeled edges, traversed from lexical seed matches.
Automatic observation capture through agent lifecycle hooks agentmemory It records what the agent did via hooks, compresses it into observations, and serves them back over a large MCP tool surface.

Basic Memory is the closest match in this list. Both are local-first, expose MCP tools, and keep human-readable markdown as durable data. The difference is where each product draws its boundary:

  • hallouminate is repository infrastructure. A wiki is conventionally stored at .hallouminate/wiki/, can be reviewed in the same pull request as the code, and is searched through repo-aware corpora. Its markdown has no required note schema.
  • Basic Memory is a knowledge-management system. Its markdown format adds entities, observations, relations, and frontmatter; it supports multiple projects and optional cloud sync. Its current local search also includes semantic search, so “hallouminate has vectors while Basic Memory has only full-text search” is not a meaningful distinction.

The practical choice is therefore workflow and scope, not a claim that one search stack is universally better.

graphify sits on the opposite side of the same arrow: it derives a map from artifacts that already exist, while hallouminate stores knowledge that exists nowhere else. graphify parses source, docs, and media into a typed graph committed inside the repo (graphify-out/graph.json) and answers queries by lexically matching node labels, then traversing edges. It gives you structure on day zero with no authoring effort, but its ceiling is the artifacts’ ceiling: it cannot hold “we tried X and it failed because Y” unless someone already wrote that down — which is exactly the fact class hallouminate exists for.

The retrieval trade is mirror-image: graphify has structural expansion but no semantic matching at query time; hallouminate has hybrid semantic retrieval but only one-hop [[wikilink]] traversal via backlinks. The two compose rather than compete — graphify’s --wiki output is ordinary markdown that a [[corpus]] entry can index, so union search can cover a derived map and a hand-authored wiki side by side, with per-chunk corpus provenance telling the agent which is which.

agentmemory shares a tagline but not a category: it is an observational memory system. Fourteen lifecycle hooks auto-capture agent activity into a key-value store outside the repository (~/Library/Application Support/agentmemory), compressed into structured observations and served through roughly fifty MCP tools alongside an iii engine process, REST, stream, and viewer ports. One system remembers what happened; hallouminate retrieves what was decided.

The fault line is source of truth. agentmemory’s index is authoritative — losing it loses the memories — and its records are machine-generated artifacts inspected through a dashboard. hallouminate’s markdown is the authoritative data: reviewable in a pull request, merged by git, portable to any tool, with a disposable index rebuilt on demand. Both independently landed on hybrid RRF retrieval with optional cross-encoder rerank, so the practical difference is not search quality but what is being searched and who vouched for it.

What hallouminate deliberately does not do

Section titled “What hallouminate deliberately does not do”
  • It does not capture every agent action or conversation automatically.
  • It does not decide which facts deserve to become durable documentation; the agent or human author does.
  • It does not extract a temporal knowledge graph from conversations or events.
  • It does not provide symbol, type, or call-graph analysis for source code.
  • It does not require a hosted account or make cloud sync part of the storage model.

These constraints keep the contract small: markdown is authoritative, the index is disposable, and a repository can carry its own durable knowledge without depending on one agent vendor.