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Connect AI Coding Tools to Your Prompt Library with MCP

March 17, 20265 min readEric Campton·Founder, TeamPrompt
Code editor with AI integration
## What is MCP? MCP (Model Context Protocol) is a standard that lets AI tools connect to external data sources through a single, unified interface. Think of it like USB for AI — one plug, every tool. TeamPrompt now ships with a built-in MCP server. Once connected, your AI coding tools can search your prompt library, run DLP scans, and log usage — all without leaving the editor. ## Which tools support MCP? Any tool that supports the MCP protocol, including: - **Claude Desktop** — Anthropic's desktop app - **Cursor** — AI-powered code editor - **Windsurf** — Codeium's AI IDE - **Claude Code** — Anthropic's CLI tool - Any MCP-compatible client ## What can you do with it? TeamPrompt exposes 5 tools through MCP: ### 1. Search prompts Ask your AI tool to find prompts from your team's library. > "Search my team's prompts about onboarding" ### 2. Get prompt content Fetch the full text of any prompt by name or ID. > "Get the bug report template" ### 3. List templates Browse all your fill-in-the-blank prompt templates. > "Show me all templates with variables" ### 4. Check DLP Scan text against your organization's security rules before sending to AI. > "Check if this text has any PII or sensitive data" ### 5. Log usage Record that a prompt was used for analytics and audit compliance. > "Log that I used the code review prompt in Cursor" ## How to set it up Setup takes about 2 minutes: 1. Go to **Settings → Integrations → MCP Server** 2. Click **Create API Key** — name it something like "Cursor - Work Laptop" 3. Select which permissions the key should have (or leave all enabled) 4. Copy the **connection config JSON** that appears 5. Paste it into your AI tool's MCP settings 6. Done — your AI tool can now access your TeamPrompt workspace ### Claude Desktop config Paste the config JSON into your `claude_desktop_config.json` file: ```json { "mcpServers": { "teamprompt": { "url": "https://teamprompt.app/api/mcp", "headers": { "Authorization": "Bearer tp_live_your_key_here" } } } } ``` ### Cursor config Go to **Settings → MCP Servers → Add** and paste the same config. ## Security API keys use SHA-256 hashing — the raw key is shown once and never stored. Each key has granular scope control, so you can create read-only keys (just search and get) or full-access keys that include DLP scanning and usage logging. Keys can be revoked instantly from the settings page, and you can set optional expiration dates for temporary access. ## What this means for your team MCP turns TeamPrompt into the connective layer between your team and every AI tool they use — not just the ones the browser extension covers. Your prompts, security rules, and audit logging extend to coding tools, CLI agents, and any future MCP-compatible app. Zero additional cost. Near-zero data usage. Maximum reach.

Frequently asked questions

Which AI coding tools support MCP?

As of mid-2026: Claude Desktop, Cursor, Windsurf, Cline, Continue, and several Code OSS forks. ChatGPT does not yet support MCP. Setup is identical across supported clients — point the MCP config at https://teamprompt.app/mcp with your API key.

What does the TeamPrompt MCP server expose?

Three tool categories: (1) prompt-library search and fetch — your coding agent can pull approved templates by topic or tag, (2) DLP scan — submit a prompt and get categorized findings before sending to the LLM, (3) audit logging — every prompt executed through the agent gets logged with user, model, and detected events.

Is the MCP connection itself secure?

Yes. Authentication is via a per-user API key scoped to your workspace's RBAC. All traffic is over HTTPS. The server runs in our standard Vercel edge environment with the same rate limiting and audit logging as the rest of the API. Revoke the key in Settings → MCP Keys at any time.

Can I run prompt DLP checks from inside Cursor without manual review?

Yes — that's the default flow. The MCP server exposes a `scan_prompt` tool that Cursor calls automatically before sending any prompt to the model. If the scan returns critical findings (credentials, PHI, customer data), the agent halts and surfaces the violation to the user; otherwise it proceeds with the auto-redacted prompt.

MCP
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