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Parsley Buyer Intent Signals

Queries Parsley buyer intent, MEDDIC qualification, lead scores, conversations, and knowledge gaps through MCP.

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Install Parsley Buyer Intent Signals

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "parsley-buyer-intent-signals": {
      "command": "npx",
      "args": [
        "-y",
        "@tryparsley/mcp-server"
      ],
      "env": {
        "PARSLEY_API_KEY": "YOUR_VALUE_HERE",
        "PARSLEY_BASE_URL": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y @tryparsley/mcp-server

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 4d ago.

Overview

Parsley - Buyer Intent Signals MCP server exposes buyer intent, MEDDIC qualification, lead scoring, and conversation data from a Parsley account to AI assistants. Its eight tools cover analytics, conversation filtering and details, hot leads, intent searches, enrichment, knowledge gaps, and MEDDIC distributions. Use it to review sales signals, prepare for calls, identify follow-up priorities, or find unanswered chatbot questions. Several prompts can also coordinate with a connected CRM MCP for cross-system workflows.

Use cases

  • Review hot and warm leads each morning
  • Search conversations for MEDDIC signals and intent
  • Inspect evidence and enrichment before a sales call
  • Find unanswered chatbot questions for content planning
  • Compare qualified leads with CRM follow-up activity

Key features

  • Buyer intent and lead-score queries
  • MEDDIC evidence and aggregate summaries
  • Conversation filtering and detailed records
  • Lead enrichment for company and buying context
  • Knowledge-gap analysis
  • Optional CRM cross-MCP workflows

Tools8

What Parsley Buyer Intent Signals lets your agent do. Expand a tool for its parameters.

Self-reported~193 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

Not checked yetLast checked 4d ago

We have not completed a health check for this listing yet.

6/8 checks healthy over the last 45d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 14h ago via OSV.dev · @tryparsley/mcp-server (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

npm downloads171Package downloads in the last 30 days.
Last commit2mo agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Tools exposed8Callable tools this server registers over MCP.
Directory activity1 viewsConfig copies, upvotes, and views on AllMCPs.

How Parsley Buyer Intent Signals works

What Parsley - Buyer Intent Signals does

Parsley - Buyer Intent Signals MCP server connects an MCP-compatible assistant to data in a Parsley account. It provides access to buyer intent signals, MEDDIC qualification information, lead scores, conversation records, extracted lead context, and chatbot knowledge gaps.

The server includes eight tools. Analytics provides account-level figures such as profile views, conversation volume, lead-quality distribution, popular topics, and conversion rate. Conversation tools list records with filters, retrieve detailed records with evidence quotes and engagement data, and identify hot or warm leads. Other tools search by MEDDIC signal, intent score, or topic; group unanswered questions; return company, role, timeline, and budget context; and summarize MEDDIC signal counts and combinations.

Five predefined prompts support recurring workflows. These include a morning briefing, stale-lead review, coaching-gap analysis, content-opportunity discovery, and deal preparation. Some prompts can use a separately connected CRM MCP to compare Parsley activity with CRM activity.

How it works

The server runs as a standard MCP process and authenticates requests with a Parsley API key. An assistant can then call the available tools using natural-language requests about leads, conversations, qualification signals, or chatbot questions.

One analytics tool is available on every account. The remaining seven tools and all five prompts require conversation balance.

Cross-MCP prompts can work with CRM MCP servers for Attio, HubSpot, Salesforce, Copper, and Pipedrive. For example, a connected CRM can provide context when checking for qualified leads without recent CRM activity or preparing for a call. Each tool also accepts an optional client organization identifier for agency use; server-side membership checks limit access to data the API-key owner is authorized to view.

Setup and configuration

Create a Parsley API key at the Parsley API-key page and use an account with the chatbot enabled. The documented installation runs the published package through npx with @tryparsley/mcp-server.

Set PARSLEY_API_KEY to the account key. PARSLEY_BASE_URL is optional and defaults to https://www.parsley.id; it can be used when a different API base URL is required. Claude Desktop and Cursor examples in the README use a stdio configuration with the package command and these environment variables.

For local development, clone the repository, install npm dependencies, build the project, and start dist/index.js with PARSLEY_API_KEY set.

Tools and capabilities

Parsley - Buyer Intent Signals supports these tool categories:

  • Account analytics and conversion reporting
  • Conversation listing, filtering, and detailed inspection
  • Hot and warm lead identification with MEDDIC evidence
  • Intent, topic, and MEDDIC-signal searches
  • Unanswered-question analysis by topic and frequency
  • Lead enrichment for company, role, timeline, and budget
  • Aggregate MEDDIC signal reporting

The prompts add reusable briefing, qualification, coaching, content, and deal-preparation workflows. The stale_leads_check prompt requires a CRM MCP, while morning_briefing and other cross-MCP workflows can use CRM context when available.

Limitations and notes

Conversation-dependent tools and prompts are not available without conversation balance. CRM comparisons also require a separately configured CRM MCP. API-key access remains subject to the owner’s Parsley permissions and client-organization membership.

Read the full README View source on GitHub

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Frequently Asked Questions about Parsley Buyer Intent Signals

Parsley - Buyer Intent Signals is an MCP server that connects AI assistants to a Parsley account and exposes tools for analytics, conversations, hot leads, intent searches, lead enrichment, knowledge gaps, and MEDDIC summaries. It also provides reusable prompts for briefings, coaching, content planning, and deal preparation.

Install it by configuring your MCP client to run `npx -y @tryparsley/mcp-server` and supplying `PARSLEY_API_KEY`. Create the key from the Parsley API-key page, and use an account with the chatbot enabled.

Yes, Parsley - Buyer Intent Signals works with Cursor through a `.cursor/mcp.json` stdio configuration. Set the server command to `npx`, pass `-y @tryparsley/mcp-server` as arguments, and provide `PARSLEY_API_KEY` in the environment.

It requires `PARSLEY_API_KEY`. `PARSLEY_BASE_URL` is optional and defaults to `https://www.parsley.id`. The API key should be a Parsley live key such as `pk_live_...`.

No, `get_analytics_summary` is available on every account.

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