| FMRS | 57 / 100 · C | 76 / 100 · B |
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| Reliability | 9 / 20 | 13 / 20 |
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| Security and permissions | 11 / 20 | 14 / 20 |
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| Maintenance | 12 / 20 | 18 / 20 |
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| Documentation | 13 / 20 | 17 / 20 |
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| Setup experience | 12 / 20 | 14 / 20 |
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| Best for | - Coding agents and CLI workflows that need persistent memory across sessions and machines (Claude Code, Codex, Cursor)
- Developers building autonomous agents that need semantic, episodic, and evolving procedural memory
- Teams using LangChain, CrewAI, or OpenClaw who want a ready memory backend
- Apps that need multi-user data isolation under a single API key
- Teams wanting an account-free, folder-based memory that uses their own model provider (Anthropic, OpenAI, or Ollama)
| - Teams that want an AI assistant to directly operate on GitHub repos and collaboration workflows
- Users already in the GitHub Copilot ecosystem who want a zero-deployment remote option
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| Not for | - Single-turn chats or scenarios with no need for cross-session state
- Environments requiring a fully local setup with no SDK or CLI installed (local mode still needs pip install mengram-ai and your own model key)
- High-concurrency writes demanding whole-folder crash-atomic transactions (the folder is not a single crash-atomic transaction and external editors do not participate in the lock)
- Self-hosters expecting good extraction from models under 8B parameters or with less than an 8K context window
| - Scenarios where you don't want the assistant to have write access to repos (enable only read-only toolsets)
- Environments with strict network isolation for private repos that can't reach the official remote endpoint
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| Required permissions | - A Mengram API key sent as an Authorization: Bearer header for cloud memory reads and writes
- In cloud mode, conversations are sent to mengram.io for extraction, embedding, and retrieval
- Claude Code hooks can read session history and working state and re-inject context before and after compaction
- `mengram import claude-code` reads local Claude Code session history (the README states secrets are redacted on your machine before upload)
- The policy gate looks up learned workflows before workflow-shaped Bash commands and can be pointed at a local memory folder via MENGRAM_MEMORY_DIR
| - A personal access token (PAT) or OAuth App token; effective scope depends on the token's own permissions
- Enabling toolsets like actions/issues/pull_requests grants write access — request tokens on a least-privilege basis
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| Risks and side effects | - Cloud mode uploads conversations and file content to a third-party service, which may include sensitive data; local mode avoids this but needs your own model key
- Auto-save and auto-recall hooks read and write memory in the background, which can introduce unwanted context
- Incorrect memories get re-recalled and injected into system prompts, with a persistent effect
- Procedures evolve automatically and the policy gate can prompt before command execution, so misconfiguration may cause false alarms
- In folder mode concurrent external edits are not lock-protected and can be overwritten; local search matches words and does not use embeddings or translation
| - Write toolsets (creating/merging PRs, triggering workflows) can cause accidental changes if the token is overscoped — try a read-only toolset first
- In hosted mode, credentials travel via the Authorization header — make sure the client-to-api.githubcopilot.com connection is trusted
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| Supported clients | Claude Desktop, Cursor, Codex, Windsurf, Cline, Claude Code, OpenClaw, LangChain, CrewAI | Claude Desktop, Claude Code, VS Code, Cursor, Windsurf, JetBrains IDEs, Zed, Amp |
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| Tools | 0 | 15 |
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