Miinta Pipedrive MCP

Miinta Pipedrive MCP

Read-only MCP server for Pipedrive that provides a digest-ready sales queue with overdue follow-ups, due today activities, and deals missing next action.

Category
访问服务器

README

Miinta Pipedrive MCP v0.1

Read-only MCP (Model Context Protocol) server for Pipedrive that provides a digest-ready sales queue with:

  • Overdue follow-up activities (from a Pipedrive filter)
  • Due today follow-up activities (from a Pipedrive filter)
  • Deals missing next action (from a Pipedrive filter)

Features

  • Single Tool: miinta.sales_queue.get - Returns a comprehensive sales digest
  • Pipedrive API v2: Uses modern Pipedrive API for activities, deals, persons, organizations, and stages
  • Data Enrichment:
    • Stage names for deals
    • Contact information (email) for persons
    • Direct deal URLs with configurable company domain
    • Days overdue calculation for activities
    • Deal metadata (undone activities count, last mail times)
  • Smart Features:
    • Cursor-based pagination support
    • Bulk fetching for persons/organizations (avoids N+1 queries)
    • Caching for improved performance (configurable TTL)
    • Configurable timezone support (default: Europe/Madrid)
    • Standard MCP stdio transport for streaming communication
    • Bearer authentication for Pipedrive API
  • Flexible: Filter IDs provided per request (not hardcoded in environment)

Quick Start

  1. git clone https://github.com/alvarolloret/pipedrive-mcp.git && cd pipedrive-mcp
  2. make all
  3. Add MCP with one command (pick one): claude mcp add pipedrive -- docker run -i --rm --env-file /Users/alvarodemuller/miinta/pipedrive-mcp/.env pipedrive-mcp or codex mcp add pipedrive -- docker run -i --rm --env-file /Users/alvarodemuller/miinta/pipedrive-mcp/.env pipedrive-mcp

Configuration

Pipedrive API Token

Get your API token from Pipedrive:

  1. Go to your Pipedrive account settings
  2. Navigate to Personal preferences → API
  3. Copy your API token

Create a .env file based on .env.example:

# Required: Pipedrive API Token (Bearer token)
PIPEDRIVE_API_TOKEN=your_pipedrive_api_token_here

# Optional: Pipedrive API Base URL (default: https://api.pipedrive.com/v2)
PIPEDRIVE_API_BASE=https://api.pipedrive.com/v2

# Optional: Pipedrive Company Domain for deal URLs (default: app.pipedrive.com)
# Example: yourcompany.pipedrive.com
PIPEDRIVE_COMPANY_DOMAIN=yourcompany.pipedrive.com

# Optional: MCP Authentication Token (required if not localhost)
MCP_AUTH_TOKEN=your_mcp_auth_token_here

# Optional: Default timezone (default: Europe/Madrid)
DEFAULT_TIMEZONE=Europe/Madrid

# Optional: Cache TTL in seconds (default: 3600)
CACHE_TTL_SECONDS=3600

# Optional: Maximum items per section (default: 50)
MAX_ITEMS_PER_SECTION=50

# Optional: Transport mode - stdio, http, or sse (default: stdio)
TRANSPORT_MODE=stdio

# Optional: HTTP Server Port (default: 3000, only used if TRANSPORT_MODE is http or sse)
HTTP_PORT=3000

Required Pipedrive Filters

You need to create three saved filters in your Pipedrive account:

  1. Overdue Activities Filter: Filter for activities with done=false and due_date < today
  2. Today's Activities Filter: Filter for activities with done=false and due_date = today
  3. Deals Missing Next Action Filter: Filter for open deals without a next activity scheduled

Get the filter IDs from the Pipedrive UI or API. These will be provided when calling the tool (not in environment variables).

MCP Tool

The server exposes one tool: miinta.sales_queue.get

Input Schema (JSON Schema):

{
  "type": "object",
  "additionalProperties": false,
  "properties": {
    "filters": {
      "type": "object",
      "additionalProperties": false,
      "properties": {
        "overdue_activities_filter_id": { "type": "integer" },
        "today_activities_filter_id": { "type": "integer" },
        "missing_next_action_deals_filter_id": { "type": "integer" }
      },
      "required": [
        "overdue_activities_filter_id",
        "today_activities_filter_id",
        "missing_next_action_deals_filter_id"
      ]
    },
    "limits": {
      "type": "object",
      "additionalProperties": false,
      "properties": {
        "overdue": { "type": "integer", "minimum": 1, "maximum": 200, "default": 25 },
        "today": { "type": "integer", "minimum": 1, "maximum": 200, "default": 25 },
        "missing": { "type": "integer", "minimum": 1, "maximum": 200, "default": 25 }
      }
    },
    "timezone": { "type": "string", "default": "Europe/Madrid" },
    "now": {
      "type": "string",
      "description": "Optional ISO datetime override for deterministic testing"
    },
    "include_people_orgs": { "type": "boolean", "default": true }
  },
  "required": ["filters"]
}

Example Request:

{
  "filters": {
    "overdue_activities_filter_id": 111,
    "today_activities_filter_id": 222,
    "missing_next_action_deals_filter_id": 333
  },
  "limits": {
    "overdue": 25,
    "today": 25,
    "missing": 25
  },
  "timezone": "Europe/Madrid",
  "include_people_orgs": true
}

Example Response:

{
  "generated_at": "2026-02-16T07:45:00+01:00",
  "timezone": "Europe/Madrid",
  "sections": {
    "overdue": [
      {
        "activity_id": 123,
        "activity_subject": "Follow-up email",
        "activity_type": "email",
        "due_date": "2026-02-14",
        "days_overdue": 2,
        "deal": {
          "deal_id": 456,
          "title": "Escola X — Pilot",
          "stage_id": 3,
          "stage_name": "Conversation open neutral",
          "url": "https://yourcompany.pipedrive.com/deal/456"
        },
        "person": {
          "id": 10,
          "name": "Maria Rius",
          "email": "maria@example.com"
        },
        "org": {
          "id": 20,
          "name": "Escola X"
        }
      }
    ],
    "due_today": [],
    "missing_next_action": [
      {
        "deal_id": 789,
        "title": "Universitat Y — Training",
        "stage_id": 2,
        "stage_name": "Contact",
        "owner_id": 1,
        "undone_activities_count": 0,
        "next_activity_id": null,
        "last_outgoing_mail_time": "2026-02-10T09:12:00Z",
        "last_incoming_mail_time": null,
        "url": "https://yourcompany.pipedrive.com/deal/789",
        "person": {
          "id": 11,
          "name": "Joan Garcia"
        },
        "org": {
          "id": 21,
          "name": "Universitat Y"
        }
      }
    ]
  },
  "stats": {
    "overdue_count": 1,
    "due_today_count": 0,
    "missing_next_action_count": 1
  },
  "source": {
    "filter_ids": {
      "overdue_activities_filter_id": 111,
      "today_activities_filter_id": 222,
      "missing_next_action_deals_filter_id": 333
    }
  }
}

Architecture

  • Pipedrive Client (pipedrive-client.ts): Handles all Pipedrive API v2 interactions
    • Activities filtering with done=false, sorting
    • Deals filtering with status=open, include_fields
    • Cursor-based pagination
    • Bulk fetching for persons/organizations
  • Cache (cache.ts): In-memory caching with TTL support
  • Sales Queue Service (sales-queue.ts): Business logic for aggregating and enriching data
    • Stage name resolution
    • Days overdue calculation
    • Person/org enrichment with bulk fetching
    • Deal URL generation with company domain
  • MCP Server (index.ts): MCP protocol implementation with stdio transport

API Version

This server uses Pipedrive API v2 endpoints:

  • /v2/activities - with filter_id, done=false, sort_by=due_date
  • /v2/deals - with filter_id, status=open, include_fields
  • /v2/persons - with bulk ids parameter
  • /v2/organizations - with bulk ids parameter
  • /v2/stages - cached for stage name resolution

Error Handling

The server implements two layers of error handling as per MCP spec:

  1. Protocol errors (JSON-RPC) for invalid args/unknown tool
  2. Tool execution errors: returns isError: true with readable error messages for:
    • Pipedrive auth failures
    • Rate limit / transient upstream errors
    • Invalid filter_id / permission issues
    • Missing required parameters

Development

# Build TypeScript only
make build

# Full rebuild (clean + Docker image)
make all

# Clean compiled output
make clean

Acceptance Criteria

The server is considered "production-ready" when it:

  • ✅ Accepts three filter IDs via tool call parameters
  • ✅ Returns correct items from each filter
  • ✅ Calculates correct days_overdue in specified timezone
  • ✅ Resolves correct stage_name values from cached stage map
  • ✅ Includes person/org names when available
  • ✅ Generates valid deal links using PIPEDRIVE_COMPANY_DOMAIN
  • ✅ Handles pagination via cursor until requested limits are filled
  • ✅ Includes deal fields: undone_activities_count, last_incoming_mail_time, last_outgoing_mail_time
  • ✅ Uses bulk fetching for persons/orgs to avoid N+1 queries
  • ✅ Returns output in exact spec format with sections, stats, source

License

ISC

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选