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Alternatives to CogZ

  • A
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    Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data. Integrates directly with Obsidan.md
    38
    17,729 PyPI
    4,342
    AGPL 3.0
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    A coding agent toolkit that provides IDE-like semantic code retrieval and editing tools, enabling LLMs to efficiently navigate and modify codebases at the symbol level rather than working with entire files.
    29
    MIT
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    A lightweight, local memory server for AI coding assistants that stores durable knowledge (decisions, facts, gotchas) in a tree structure, enabling persistent context across sessions with efficient retrieval via summaries and FTS5 search.
    9
    25 npm
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    Provides coding agents with persistent local memory by exposing tools to save, search, and retrieve decisions, bugs, and context as Markdown with hybrid keyword and semantic search.
    4
    MIT

Related Servers

  • F
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    Enables AI coding agents to read and write persistent, local-first memory across sessions and projects, with semantic search, global guidelines, and optional autonomous task execution.
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    Local-first engineering memory and code-graph tools for coding agents. Supports private session handoffs, code-cited knowledge, repository graph inspection, and optional Git-backed team sharing.
    25
    605 npm
    26
    AGPL 3.0
  • F
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    Enables AI coding agents to store and retrieve persistent project and cross-project memories via semantic search, so decisions, preferences, error patterns, and guidelines survive across sessions. Optionally supports autonomous task execution built on the same local-first knowledge store.
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  • F
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    Provides AI coding agents with a local-first persistent memory layer they can read and write during sessions, storing decisions, preferences, error patterns, and research per project or globally. Enables semantic and keyword search, formatted context recall, and cross-project guideline surfacing without API keys or cloud storage.
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TDQS

A3.9/5.0

Scored across 15 tools

Disambiguation4/5

Most tools target distinct operations such as status checks, search, context assembly, knowledge lifecycle management, and code-graph analysis. The main overlap is between list_entities and query_entities, and to a lesser extent search/query_entities, but the descriptions largely clarify when each should be used.

Naming Consistency4/5

Names are consistently snake_case and predominantly follow a verb_noun pattern (get_status, list_entities, create_entity, get_callers, etc.). A few deviations are single-verb or less patterned names like search and consolidate, but the overall convention is predictable.

Tool Count5/5

At 15 tools, the set is well-scoped for a knowledge/code-graph server covering status, retrieval, lifecycle management, and graph queries. Each tool maps to a meaningful operation, including hook-driven and housekeeping tools, without excessive surface area.

Completeness4/5

The server covers core knowledge lifecycle (create, update, reject, verify, consolidate), retrieval (search, query_entities, get_context), and code-graph analysis (get_callers, get_impact, find_orphans). Minor gaps exist, such as no direct get_entity-by-id for full content and no outgoing dependency/callee query, but agents can work around them via search and existing browse tools.

Maintenance

ActivityActive
ResponsivenessNo issues