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Compare scores, permissions, risks, and fit in one decision-focused table.

DimensionJina AI Remote MCP ServerJina AI's official remote MCP server for web reading, search, and embeddings/rerankingCompartmentEncrypted, fully offline long-term memory for AI agents
FMRS64 / 100 · C75 / 100 · B
Reliability7 / 2012 / 20
Security and permissions13 / 2016 / 20
Maintenance12 / 2014 / 20
Documentation18 / 2018 / 20
Setup experience14 / 2015 / 20
Best for
  • Developers who want to give an LLM real-time web search and reading capability
  • Researchers doing academic literature review across arXiv and SSRN
  • Teams needing semantic deduplication or classification of text/image sets
  • Users with a Jina API key who want one remote MCP server usable across multiple clients
  • Individuals or teams who prioritise privacy and offline operation and do not want data leaving the machine
  • Users who share memory across multiple MCP clients such as Claude Code, Claude Desktop, Hermes Agent, OpenClaw, Cursor, Codex and Gemini CLI
  • Scenarios that need encrypted storage, a hash-chained audit log and verifiable vault migration
  • Users who want low-latency recall, a bundled embedding model and no extra LLM calls inside the memory layer
Not for
  • Fully offline or air-gapped environments with no outbound network access
  • Users unwilling to obtain a Jina API key, since most tools require one for full access and unauthenticated use is rate-limited
  • Latency-sensitive workflows, since tools like search_web_deep can take 2-20 seconds per call
  • Users who need cloud multi-device sync or a hosted team memory service; moving between machines means locking the vault and copying the file
  • Users who expect the server itself to run an LLM that extracts facts and decides what to remember; Compartment explicitly keeps no LLM inside and leaves that to the host model
  • Users who cannot keep a passphrase safe or who need a recovery path if it is lost, since Compartment never generates a password, seed or recovery phrase
  • Deployments that require network transports such as SSE or streamable-http; this server is stdio only and opens no ports
Required permissions
  • An optional or required Jina API key (Bearer token) for accessing the Reader/Embeddings/Reranker APIs and higher rate limits
  • Outbound network access from the server to target URLs, search engines, and Jina's cloud APIs
  • Read and write the vault file under the user's home directory, by default ~/.compartment/memory.vault, and its sibling settings file
  • Access the session directory holding the unlock credential (configurable with COMPARTMENT_SESSION_DIR), which also carries the shared embedding process's Unix socket
  • Optionally use the macOS keychain (compartment unlock --keychain is an explicit opt-in, and it survives reboots)
  • Write or merge an mcpServers entry into each MCP client's own configuration file, taking a byte-exact backup first
  • Install a PostToolUse hook for Claude Code that captures memory files the agent writes
  • Serve a read-only dashboard on 127.0.0.1 behind a one-time random URL token
Risks and side effects
  • This is a hosted remote server at mcp.jina.ai — queries and fetched page content pass through Jina's cloud infrastructure
  • API keys stored in plaintext config files or environment variables can be exposed if configs are shared or leaked
  • Rate limits apply to tools used without an API key, which can bottleneck heavy usage
  • Some tools (e.g. search_web_deep) have noticeably longer response times, which can affect interactive workflows
  • A leaked passphrase means the encrypted content can be decrypted; Compartment generates no recovery phrase and cannot recover a lost passphrase
  • Enabling the memory_unlock tool places the passphrase in the model's context, which is why it is off by default
  • If a 2FA keyfile is lost, for example a USB stick, the vault cannot be opened even with the passphrase
  • `export --plaintext` writes the vault as unencrypted JSONL, so that file must be handled carefully
  • Memory content can come from untrusted sources; recall wraps memories with a notice that they are stored data and content can be marked quarantined, but the host agent must still treat memory as data to limit prompt-injection risk
  • The capture hook and client integration write into the user's own settings files, although the implementation backs up and merges rather than replacing
Supported clientsCursor, LM Studio, Claude Code, Claude Desktop, Codex, WindsurfClaude Desktop, Claude Code, Hermes Agent, OpenClaw, Cursor, VS Code, Codex, Gemini CLI, Cline, Roo Code, Zed, OpenCode, LM Studio, AnythingLLM, BoltAI, Goose, Kiro
Tools2214