NDASentry
Anonymous NDA risk analysis exposed as MCP tools. Designed for AI agents to review NDAs on behalf of users — flag risky clauses, return a structured risk report, $9 per full report via Stripe. No account required.
README
NDASentry MCP Server
Anonymous NDA risk analysis for AI agents. $9 per report. No signup, no account, no data retention.
NDASentry exposes a multi-stage NDA risk analysis pipeline as MCP tools so any AI agent (Claude Desktop, Cursor, Cline, etc.) can review NDAs on behalf of its user — discover risky clauses, flag missing protections, return a structured risk report — without asking the user to leave the agent, create an account, or wait for a lawyer.
The wedge: every other legal MCP server in this space requires an account, an enterprise login, or attorney-in-the-loop review. NDASentry is designed to be the simplest path for a personal AI agent: call anonymously, pay $9 with a card, get a structured analysis in under a minute.
What it does
Two tools:
-
preview_nda_risk(pdf_base64, filename) — Free preview. Stages the NDA, runs cheap-stage detection (regex-based clause finding, no LLM calls), returns a clause-level summary plus a Stripe payment link. Safe to expose to anonymous agent traffic; zero LLM cost on the preview path.
-
get_nda_report(session_token) — Paid full report. Polls payment status, then runs the full multi-stage LLM pipeline (qualifier, detector, scorer, critic, synthesizer, decision policy) and returns structured JSON with clause-level risk findings, aggressive-clause signals, missing protections, a critique, and a recommended action.
The full pipeline output is designed for agent consumption — flat structured JSON, every clause carries risk level, evidence, and reasoning, so agents can filter, summarize, or route based on what their user cares about.
Quick start (hosted)
Point your MCP client at the public hosted endpoint:
https://nda-mcp-production.up.railway.app/mcp
Claude Desktop config
Add to claude_desktop_config.json:
{
"mcpServers": {
"ndasentry": {
"url": "https://nda-mcp-production.up.railway.app/mcp",
"transport": "streamable-http"
}
}
}
Restart Claude Desktop. The two tools will appear in the agent's tool catalog.
Example agent prompt
Review this NDA and tell me if there is anything I should push back on before signing. [attach NDA PDF]
The agent calls preview_nda_risk first, returns a preview plus a payment URL. You pay $9 in your browser. The agent calls get_nda_report and returns the full analysis.
Self-host
For users who want their own instance, or local development:
git clone https://github.com/valtirman/ndasentry-mcp.git
cd ndasentry-mcp/mcp_server
python -m venv .venv-mcp
source .venv-mcp/bin/activate
pip install -r requirements.txt
export NDASENTRY_BACKEND_URL=https://ndasentry.ai
python -m mcp_server.server
The server listens on http://localhost:1966/mcp by default. Point your MCP client at it:
{
"mcpServers": {
"ndasentry": {
"url": "http://localhost:1966/mcp",
"transport": "streamable-http"
}
}
}
Configuration
| Env var | Default | Purpose |
|---|---|---|
| NDASENTRY_BACKEND_URL | http://localhost:8001 | Backend API that runs the analysis pipeline |
| PORT | 1966 | Port the MCP server binds to |
| MCP_ALLOWED_HOSTS | (empty) | Comma-separated production hosts to add to DNS rebinding allowlist |
| MCP_ALLOWED_ORIGINS | (empty) | Comma-separated production origins to add to DNS rebinding allowlist |
The backend (ndasentry.ai by default for the hosted version) handles document analysis and Stripe payment verification. The MCP server is a thin protocol adapter that does not reimplement any pipeline logic. The same backend serves the web product at https://ndasentry.ai.
Tools reference
preview_nda_risk
Input:
- pdf_base64 (string): base64-encoded PDF bytes, max 10 MB
- filename (string): the PDF filename
Output: JSON with session_token, payment_url (Stripe link with the session token bound as client_reference_id), clause_summary, missing_required_clauses, a labeled sample clause showing the shape of a paid analysis, and a disclaimer.
get_nda_report
Input:
- session_token (string): from the preview_nda_risk response
Output: Full structured AnalysisReport JSON with clauses, risk scores, critique, completeness, qualification, aggressive-clause signals, recommended action, and disclaimer. If payment is not yet complete, returns a polling status response instead.
Disclaimer
NDASentry is a contract risk screening tool, not a law firm. Output is not legal advice and does not create an attorney-client relationship. For binding legal interpretation or high-stakes decisions, consult licensed counsel.
Privacy
The hosted backend at ndasentry.ai is designed around an "evaporates" model:
- Documents are processed in memory only, never written to disk
- Reports are cached in RAM for 5 minutes after generation, then deleted
- No account, no email collection, no document retention
About
Built by Val Tirman at FrontRange Mountain AI LLC. Solo indie effort. The web product runs at https://ndasentry.ai; this MCP server is the agent-facing channel on the same backend.
If you build something with NDASentry MCP, drop a note: frontrangesupport@gmail.com. Genuinely interested in what agents do with this.
License
MIT — see LICENSE file in the repository root.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.