Cursor Chat History MCP

Analyzes local Cursor chat history to extract development patterns, usage insights, and coding best practices with tools for searching conversations, generating analytics, and exporting data in multiple formats for personalized development assistance.

Skills

Explore the skills and capabilities of this skillset.

get_system_info

Get system information and utilities for AI assistants. Provides current date, timezone, and other helpful context that AI assistants may not have access to. Use this when you need reference information for date filtering, time-based queries, or other system context.

get_conversation

Retrieves the complete content of a specific Cursor conversation including all messages, code blocks, file references, title, and AI summary. WORKFLOW TIP: Use conversation IDs from list_conversations, search_conversations, or analytics breakdowns (files/languages arrays contain conversation IDs). Use summaryOnly=true to get enhanced summary data without full message content when you need to conserve context.

list_conversations

Lists Cursor chats with summaries, titles, and metadata ordered by recency. **HIGHLY RECOMMENDED: Use projectPath parameter to filter conversations by specific project/codebase** - this dramatically improves relevance by finding conversations that actually worked on files in that project. Returns conversation IDs for use with get_conversation tool. WORKFLOW TIP: Start with projectPath filtering for project-specific analysis, then call get_conversation with specific IDs from results. Includes AI-generated summaries by default. Supports date range filtering (YYYY-MM-DD format).

search_conversations

Searches through Cursor chat content using exact text matching (NOT semantic search) to find relevant discussions. **WARNING: For project-specific searches, use list_conversations with projectPath instead of this tool!** This tool is for searching message content, not project filtering. **WHEN TO USE THIS TOOL:** - Searching for specific technical terms in message content (e.g., "useState", "async/await") - Finding conversations mentioning specific error messages - Searching for code patterns or function names **WHEN NOT TO USE THIS TOOL:** - ❌ DON'T use query="project-name" - use list_conversations with projectPath instead - ❌ DON'T search for project names in message content - ❌ DON'T use this for project-specific filtering Search methods (all use exact/literal text matching): 1. Simple text matching: Use query parameter for literal string matching (e.g., "react hooks") 2. Multi-keyword: Use keywords array with keywordOperator for exact matching 3. LIKE patterns: Advanced pattern matching with SQL wildcards (% = any chars, _ = single char) 4. Date range: Filter by message timestamps (YYYY-MM-DD format) IMPORTANT: When using date filters, call get_system_info first to know today's date. Examples: likePattern="%useState(%" for function calls, keywords=["typescript","interface"] with AND operator.

export_conversation_data

Export chat data in various formats (JSON, CSV, Graph) for external analysis, visualization, or integration with other tools. **TIP: Use filters.projectPath to export only project-specific conversations** for focused analysis of a particular codebase. Use this to create datasets for machine learning, generate reports for stakeholders, prepare data for visualization tools like Gephi or Tableau, or backup chat data in structured formats.

find_related_conversations

Find conversations related to a reference conversation based on shared files, folders, programming languages, similar size, or temporal proximity. Use this to discover related discussions, find conversations about the same codebase/project, identify similar problem-solving sessions, or trace the evolution of ideas across multiple conversations.

get_conversation_analytics

Get comprehensive analytics and statistics about Cursor chats including usage patterns, file activity, programming language distribution, and temporal trends. **BEST PRACTICE: Use projectPath parameter for project-specific analytics** - this analyzes only conversations that worked on files in that project, providing much more relevant insights for understanding coding patterns, file usage, and development activity within a specific codebase. WORKFLOW TIP: Always include "files" and "languages" in breakdowns - these contain conversation IDs in their arrays that you can immediately use with get_conversation tool. Use includeConversationDetails=true when you need the full conversation ID list and basic metadata for follow-up analysis.

extract_conversation_elements

Extract specific elements from conversations such as file references, code blocks, programming languages, folder paths, metadata, or conversation structure. Use this to build knowledge bases, analyze code patterns, extract reusable snippets, understand project file usage, or prepare data for further analysis and documentation.

Configuration

Customize the skillset to fit your needs.
MCP Server

Connect to MCP Server

Cursor Chat History MCP

Email 营销助手
自动寻找潜在客户并发送为期3天的跟进邮件序列。
品牌设计师
一款专为初创数字产品设计的品牌营销 AI 助手,帮助您快速生成适合 Product Hunt、AppSumo 等平台的在线推广材料,涵盖视觉创意、推广标语、品牌语调和卖点传达
需求文档撰写助手
告诉我您的产品或功能想法 - 我将帮助您创建全面且详细的需求文档,涵盖用户故事、验收标准、技术规范等内容。
客服文档助手
AI 助手协助客服团队创建高质量的支持文档,包括常见问题、工单回复、道歉信和标准操作程序。引导您创建内部资源和面向客户的材料。
AI 写作助手
告诉我有关 AI 产品或品牌的信息 - 我将撰写吸引人的营销文案、文章和社交媒体帖子,根据您的品牌声音和产品细节量身定制,并附上相关链接和插图。
工单管理员
收集、分析和管理来自表单和数据库的支持工单,帮助您高效地跟踪、优先处理和回应。
X/Twitter 助手
一个 AI 驱动的 Twitter 助手,帮助内容创作者将 AI 产品体验转化为病毒式推文 - 具有自动润色、智能研究和一键发布功能。
Google 分析师
逐步指南,教您如何将 Google Analytics 4 (GA4) 属性连接到 Google 分析师代理。涵盖创建 Google Cloud 服务账户、启用 Analytics Data API、授予 GA4 查看者访问权限,以及配置代理以支持会话、用户、跳出率、转换等指标。非常适合快速在 Bika.ai 中设置 GA4 数据报告。
Github issues 助手
Github Issues 助手是一个 AI 智能体,用于简化 GitHub issues的管理。它可以直接在存储库中简化创建、跟踪和优先处理错误、任务或功能请求的过程。非常适合团队使用,确保一致的格式,自动化重复步骤,并与开发管道集成。

Frequently Asked Questions

Bika.ai是免费使用的吗?
是什么让 Bika.ai 如此独特?
一句话快速介绍:什么是Bika.ai?
"BIKA" 这个缩写单词代表什么意思?
Bika.ai是怎么做到AI自动化做事的?
Bika.ai与Kimi、ChatGPT等AI助手有什么区别?
Bika.ai与多维表格有什么区别?
Bika.ai在单表数据量、关联引用变多后,如几万行、几十万行,会卡吗?
Bika.ai中的"空间站"是什么?
付款后我拥有多少个付费空间?
什么是"资源"?
Bika.ai的团队是怎样”吃自己的狗粮“(应用自己的产品)的?
Bika.ai如何帮助提高工作效率?
Bika.ai 的AI自动化功能有哪些特点?
Bika.ai 中的自动化模板是什么?
Bika.ai 是否支持团队协作及权限功能?
Bika.ai是否只适合个人使用?企业团队会不适合?

Embark on Your AI Automation