| FMRS | 59 / 100 · C | 80 / 100 · B | 79 / 100 · B |
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| Reliability | 10 / 20 | 14 / 20 | 12 / 20 |
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| Security and permissions | 12 / 20 | 16 / 20 | 16 / 20 |
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| Maintenance | 12 / 20 | 17 / 20 | 18 / 20 |
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| Documentation | 11 / 20 | 15 / 20 | 18 / 20 |
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| Setup experience | 14 / 20 | 18 / 20 | 15 / 20 |
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| Best for | - Developers who use several MCP-compatible AI coding tools and are tired of re-explaining themselves.
- Users who want memory and identity data to stay on their own machine, inspectable and editable.
- Individuals or small teams long-term-accumulating quality standards, architecture decisions, and technical lessons.
- Vibe-coding workflows that need continuity across sessions, tools, and projects.
- Users who accept human review gates in exchange for local data sovereignty.
| - Developers using fast-moving frameworks/libraries worried about the AI suggesting stale code
- Scenarios wanting zero-config documentation lookup
| - Developers auditing NPM dependencies within AI workflows
- Teams performing supply chain security assessments
- Users of Claude Desktop, Cursor, or VS Code
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| Not for | - Multi-person collaboration, team-shared memory, or centrally managed server deployments (this is a personal identity layer).
- Anyone needing vendor SLAs, enterprise support, or a commercial license (AGPL-3.0, no separate commercial license).
- Storing passwords, API keys, or customer PII — the project explicitly advises against it.
- Users whose primary need is agent task memory/session history and who have already chosen Mem0/Zep/Letta-style tools.
- Scenarios demanding hardened access control over plaintext local files: restricted_fields and the governance layer are not encryption or a true ACL.
| - Looking up internal/private codebase documentation (Context7 targets publicly published open-source libraries)
- Cases needing very high coverage of obscure, niche libraries (coverage depends on what Context7's platform has indexed)
| - Projects outside the NPM ecosystem (e.g., pure Python/Go)
- Environments without network access to deps.dev, OSV.dev, and the npm registry
- Scenarios requiring maintenance by an official upstream vendor
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| Required permissions | - Read and write JSON/Markdown files under the local Engram data folder (default ~/.engram/).
- Write AI-client MCP config and instruction files during engram setup, only after your confirmation (backed up first; decline leaves them untouched).
- Write a local-only audit log at ~/.engram/audit.log, enabled by default (opt out with ENGRAM_AUDIT=0).
- Optional: read_web_content fetches a URL you provide, via a local sidecar or the built-in reader.
- Optional: ENGRAM_TOOLS=all exposes all 59 tools to the model, including owner/admin export, import, and trust-management interfaces.
- Optional: remote SSE mode requires ENGRAM_AUTH_TOKEN and should sit behind a TLS reverse proxy.
- Optional: telemetry is off by default; enabling remote telemetry or feedback is separate explicit opt-in and sends counts only.
| - Usable without an API key (subject to a free-tier rate limit); CONTEXT7_API_KEY is an optional credential for higher quota
- Read-only documentation lookup — no code execution or local filesystem access involved
| - Network access to the NPM registry and external services (deps.dev, OSV.dev, OpenSSF, npms.io, GitHub)
- Read access to workspace lockfiles (pnpm-lock.yaml, package-lock., yarn.lock) for cache invalidation
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| Risks and side effects | - Data is plaintext JSON/Markdown by default, so any process that can read ~/.engram/ can read your data; field-level encryption is optional, not the default.
- The project explicitly warns against storing passwords, API keys, or client PII in Engram.
- restricted_fields only reduces what is emitted in cold-start context — it is not encryption or a real ACL.
- Caller identity comes from MCP environment variables rather than cryptographic authentication, so governance is a practical local policy boundary, not a hardened sandbox; the MCP spec does not pass tool identity.
- Export outputs (export_engram, get_identity_card, export_knowledge_report) contain full or broad content and should be treated as sensitive files.
- import_engram mutates the local store: always preview with dry_run=True first; applying requires explicit --apply --yes.
- Concurrent writes rely on a file lock plus atomic replace; network-filesystem edge cases are not guaranteed.
- Playbook auto-extraction redacts sensitive info before staging (keys, tokens, absolute paths, emails), but drafts remain untrusted until you confirm them.
- Remote deployment without proper HTTPS and token handling can expose identity data.
| - The free tier has limited quota — high-frequency use may hit rate limits
- Documentation content comes from Context7's platform index, so its accuracy and freshness depend on that platform's crawl cadence
| - Third-party READMEs and changelogs are untrusted external content; they are wrapped in tags with _meta flags but should still be handled cautiously
- Depends on availability and accuracy of external services
- Batch requests are capped at 25 packages to prevent registry enumeration; larger sets require batching
- Third-party open source project, not officially maintained by NPM or Anthropic
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| Supported clients | Claude Code, Codex, Cursor, Claude Desktop, Hermes, OpenClaw, Windsurf, GitHub Copilot, Cline, Roo Code, Amazon Q, Augment, Zed, Trae, Tencent CodeBuddy, ChatGPT / Gemini / Kimi (Markdown identity card) | Claude Code, VS Code, Cursor, Cline, Amp | Claude Desktop, VS Code, Cursor, Smithery.ai |
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| Tools | 58 | 2 | 19 |
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