Myco Brain vs Two-tier-memory

Myco Brain and Two-tier-memory are both agent frameworks tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Myco Brain

The core mechanic is deterministic writes: the application code writes facts to Myco's Postgres store, not the LLM, so every stored fact carries a source document, a confidence score, and a full audit trail queryable via brain_why. One MCP server exposes that memory to Claude Code, Cursor, Codex, Windsurf, and any other MCP-compatible client simultaneously — write from Claude Desktop, retrieve from Cursor, no sync step required. The vendor publishes a 500-question LongMemEval result and a recall@5 figure using a recency reranker, both on the full benchmark set. The hard ceiling appears when your agents need to act on what they remember — Myco stores and retrieves facts; it does not plan, route, or execute tasks, so orchestration logic lives elsewhere.

Two-tier-memory

The library implements what the repo calls the 'two-tier fix': structured storage in a local SQLite database, with semantic or keyword queries pulling back only the relevant rows instead of the entire memory corpus. The core workflow is a single Python file and a SQL schema — add a memory, query a memory, done. It runs entirely on-device with no external API calls. The wall you hit is expressiveness: the schema is fixed, so teams with complex memory taxonomies end up forking the schema or layering their own abstraction on top. At that point you are maintaining a fork.

Attribute	Myco Brain	Two-tier-memory
Pricing	Free	Free
Free trial	No	No
Open source	Yes	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	Postgres, Docker, MCP clients	Python, SQLite
Released	2026	—
Pros	Deterministic write path means the LLM never authors the facts stored in memory, so every retrieved fact links to a source document and confidence score — which means regulated teams get an audit trail without building one themselves. One MCP server shared across all connected clients, so a fact written from Claude Desktop is immediately readable by a Cursor agent without a sync job or intermediate API call. Full-stack boot with docker compose and no required API keys, so teams evaluate and prototype without committing credentials or cloud spend before the architecture is validated. Content-hash deduplication on document ingestion, so re-importing the same ChatGPT or Claude export twice does not corrupt or inflate the memory store. Graph queries over entity relationships via the built-in tools, so agents can retrieve not just isolated facts but the web of connections between people, decisions, and documents in the store.	Queries the SQLite store for only the relevant memory entries rather than loading the full history into context, so the agent's effective memory scales with the size of the database rather than the size of the context window. Entirely local and dependency-light — no API keys, no network calls, no managed service — which means the memory layer cannot go down because a third-party endpoint is unavailable. MIT license with full source in a single Python file, so you can read exactly what happens to your stored data and modify the retrieval logic without waiting on a vendor. CLI-driven interface means you can add or query memories from shell scripts, editor plugins, or agent tool calls without importing a framework. Persistent across sessions by default via SQLite, so a solved problem recorded in one session is available in every subsequent session without any additional configuration.
Cons	Myco stores and retrieves facts — it has no planner, no task router, and no execution loop. Teams building agents that need to act on retrieved memory must implement that logic themselves, which means maintaining a separate orchestration layer alongside the memory layer. The self-hosted path requires running Postgres 16 with pgvector and managing that infrastructure. Teams without existing Postgres ops experience hit configuration and maintenance overhead that the single docker compose up does not eliminate long-term. Semantic search requires a local Ollama instance or an external embedding provider; teams without GPU-capable self-host infrastructure who want semantic recall beyond full-text search are blocked until the cloud offering exits beta — at which point they are evaluating a hosted product with a waitlist rather than a drop-in replacement. No API surface is exposed outside the MCP protocol, so teams whose agents run outside MCP-compatible clients cannot integrate without building a custom MCP wrapper — teams with that constraint typically move to a vector database with a standard REST or gRPC API instead.	The schema ships with a fixed structure targeting solved coding problems and project decisions. Teams whose memory needs include different record types — hierarchical documentation, multi-entity relationships, or domain-specific metadata — hit the schema ceiling immediately and must fork and migrate, at which point they own all future schema evolution. There is no server, no sync layer, and no multi-agent access model. A team with more than one agent process, or a developer working across multiple machines, gets no shared state — each environment has its own isolated database, and keeping them consistent is a manual problem. At the point where a team needs semantic vector search rather than keyword or structured queries — typical once the memory corpus grows large and queries become fuzzy — this library provides no embedding or vector retrieval path. That is the condition under which teams move to a dedicated vector database or a memory framework like Mem0 instead.

Bottom line

Myco Brain and Two-tier-memory are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between Myco Brain and Two-tier-memory?

Myco Brain is Free and open source, while Two-tier-memory is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Myco Brain better than Two-tier-memory?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.