Nefesh — Real Time Human State Awareness for AI vs Threadline MCP

A side-by-side look at the Nefesh — Real Time Human State Awareness for AI and Threadline MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

Nefesh — Real Time Human State Awareness for AI logoNefesh — Real Time Human State Awareness for AICommunication · Remote HTTP/SSEFuses biometric signals into a stress score (0-100) for AI adaptation. MCP + A2A native.64GoodAuth: not declaredThreadline MCP logoThreadline MCPCommunication · Local subprocess (stdio)Agent-to-agent messaging relay. Discover agents, send messages, and receive replies. Zero-config.49FairAuth: not declared

Verdict: choose Nefesh — Real Time Human State Awareness for AI for communication work over a hosted endpoint; choose Threadline MCP for communication as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

Nefesh — Real Time Human State Awareness for AI logoChoose Nefesh — Real Time Human State Awareness for AI when

  • You need dedicated capabilities in the Communication domain.
  • You prefer a remote HTTP/SSE transport.
  • You want tools like get_human_state, ingest, get_trigger_memory.
Explore Nefesh — Real Time Human State Awareness for AI

Threadline MCP logoChoose Threadline MCP when

  • You need dedicated capabilities in the Communication domain.
  • You prefer a local stdio subprocess transport.
Explore Threadline MCP

Feature & specification comparison

Rows where the two servers differ are marked.

SpecNefesh — Real Time Human State Awareness for AI logoNefesh — Real Time Human State Awareness for AIThreadline MCP logoThreadline MCP
CategoryCommunicationCommunication
Quality signal64/100 · Good49/100 · Fair
Install commandConfirmedConfirmed
TransportRemote HTTP/SSELocal subprocess (stdio)
AuthNot declaredNot declared
PricingNot declaredNot declared
Required env varsNone listedNone listed
Verified ownerCommunity listingCommunity listing
GitHub stars084
Directory activity 1 views 0 installs 0 upvotes 3 views 0 installs 0 upvotes
Tools7Not listed

Tools & capabilities

Nefesh — Real Time Human State Awareness for AI tools 7

  • get_human_stateGet current unified human state for a session. Call this before generating important responses. Returns: - state: calm | relaxed | focused | stressed | acute_stress - stress_score: 0-100 (lower = calmer) - confidence: 0.0-1.0 (based on signal quality and device type) - suggested_action: maintain_engagement | simplify_and_focus | de-escalate_and_shorten | pause_and_ground - action_reason: human-readable explanation of why this action was suggested - adaptation_effectiveness (on 2nd+ call): shows whether your previous suggested_action actually reduced stress — contains previous_action, stress_delta, and effective boolean. Use this to self-improve. Use suggested_action to adapt your response: calm/relaxed = full complexity, focused = shorter and structured, stressed = max 2 sentences, acute_stress = one grounding sentence only. Requires a prior ingest call to have data. Not a medical device.
  • ingestSend biometric signals from any sensor, get unified state back. Required: session_id + timestamp (ISO 8601) + at least one signal. Send whatever you have — the API fuses all signals into one state. Common signals (highest impact): - heart_rate (bpm, 30-220) + rmssd (ms) — cardiovascular - tone: calm | tense | anxious | hostile — vocal - sentiment: -1.0 to 1.0 — textual - expression: relaxed | neutral | tense — visual For trigger memory (cross-session psychological tracking): - Include subject_id (consistent per user, hashed) Returns same fields as get_human_state plus signals_received list and topics_detected (if conversation text was included). source_device is optional but improves confidence scoring. Not a medical device.
  • get_trigger_memoryRetrieve psychological trigger profile for a subject. Returns which conversation topics consistently cause stress (active triggers) and which have been resolved over time. - active triggers: topics where stress was elevated across multiple sessions. Tread carefully. - resolved triggers: topics where stress has decreased. Safe to explore deeper. Each trigger includes observation_count, avg_score, peak_score, and last_seen. Requires prior ingest calls with the same subject_id. Not a medical device.
  • get_session_historyGet state history for a session over time. Returns timestamped datapoints with stress_score, state, and heart_rate for each observation. Includes an overall trend: rising | falling | stable. Use minutes parameter to control the lookback window (default: 5, max: 60). Useful for detecting stress patterns during a conversation. Not a medical device.
  • delete_subjectPermanently delete all sessions and trigger memory for a subject. Irreversible. Only call when the user explicitly requests this deletion.
  • request_api_keyStart free API key authorization; no existing API key needed. Returns a verification_url. Ask the user to open that URL in their browser, enter their own email, then open the verification email and confirm access for their agent. This tool does not accept email addresses and does not send email. Do not choose, invent, or submit an email on the user's behalf. Poll check_api_key_status with the returned request_id at the supplied interval. Stop if the request expires. Never create new requests in a loop.
  • check_api_key_statusCheck a pending API key authorization using its request_id. Use request_id exactly as returned by request_api_key, never an email. Poll every 10 seconds. awaiting_user means the user must open the URL; pending means email verification is still required. ready returns the API key once only. Store it and include it in all subsequent HTTP calls. Stop on expired; ask the user before starting another authorization.

Threadline MCP tools

No tool names declared yet. Check the project README from the listing page.

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

Nefesh — Real Time Human State Awareness for AI

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "nefesh-real-time-human-state-awareness-for-ai": {
      "url": "https://mcp.nefesh.ai/mcp"
    }
  }
}

Threadline MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "threadline-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "instar"
      ]
    }
  }
}

Frequently asked questions

Nefesh — Real Time Human State Awareness for AI is categorized under Communication and uses a remote HTTP/SSE transport. Threadline MCP belongs to Communication and uses a local stdio subprocess. Pick Nefesh — Real Time Human State Awareness for AI for communication work and Threadline MCP for communication.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.

Nefesh — Real Time Human State Awareness for AI has no declared pricing — check the project's own site. Threadline MCP has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add nefesh-real-time-human-state-awareness-for-ai and threadline-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, Nefesh — Real Time Human State Awareness for AI has a quality signal of 64/100 (Good) with 1 views, 0 installs and 0 GitHub stars. Threadline MCP has 49/100 (Fair) with 3 views, 0 installs and 84 GitHub stars.