Kage
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Alternatives to Kage
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceMCP server that gives coding agents persistent, verified memory of codebase decisions, conventions, and skills, with evidence-based claims that are re-checked via git hooks and human-gated review. Enables memory search, propose/approve, chat harvesting, and critique across MCP-compatible tools.21112 npm1MIT

MemForgeofficial
FlicenseNot gradedqualityBmaintenanceGives AI agents a shared, cited memory of team knowledge built from docs, tickets, chat and confirmed decisions, exposing search, memory retrieval and source lookup over MCP. Agents can recall relevant conventions and evidence, and save new memories after user confirmation, across Claude Code and Codex sessions.24-- AlicenseAqualityAmaintenanceMCP-native, local-first memory for coding agents that turns real sessions into reusable decisions, gotchas, and domain knowledge.17499 PyPI7MIT
- AlicenseNot gradedqualityCmaintenanceProvides AI coding agents with deterministic, attestable org memory via an MCP server, enabling automatic recall of relevant facts on every prompt, loss-proof capture of learnings, and curated promotion of verified facts to a tenant-isolated memory store.Apache 2.0
- AlicenseAqualityAmaintenanceEnables AI coding agents to share a persistent, git-backed team memory, automatically committing and syncing decisions, solutions, gotchas, statuses, and handoffs across projects and MCP clients.301MIT
- AlicenseNot gradedqualityAmaintenanceGives AI coding agents persistent, cross-session memory by storing task insights as interlinked markdown knowledge cards and recalling relevant ones before new work begins. Uses plain files and git sync instead of a vector database or embeddings, and exposes this through MCP tools for Claude Code, Cursor, VS Code Copilot, Codex, Windsurf, and other clients.13 npmISC
TDQS
Scored across 11 tools
Most tools map cleanly to distinct capabilities: learn/supersede/feedback handle memory lifecycle, context/decisions/docs_search handle retrieval, refresh/pr_check handle repository state, and risk/dependency_path/skills handle analysis and export. A couple of adjacent pairs (learn vs. skills, refresh vs. pr_check) could be confused at first glance, but the descriptions draw clear read/write and capture/codify boundaries.
All tools share the kage_ prefix and snake_case, and most suffixes are descriptive noun phrases such as context, risk, dependency_path, decisions, docs_search, pr_check, and skills. The pattern is slightly inconsistent because a few suffixes are bare verbs like refresh, supersede, and learn, but the overall convention remains predictable and readable.
Eleven tools is well-scoped for a repo-memory and code-graph assistant; each tool covers a distinct part of the workflow from capture and recall to risk analysis, indexing, PR readiness, and skill export. There is no obvious filler or redundant tool.
The set covers the core memory lifecycle (learn, context, supersede, feedback) plus supporting analysis (risk, dependency path, docs search) and repository operations (refresh, pr_check, skills). Minor gaps exist, such as no explicit packet-list/search tool or skill-management/removal, but agents can work around them.