MCP Think Tank
Provides AI assistants with enhanced reasoning capabilities through structured thinking, persistent knowledge graph memory, and intelligent tool orchestration for complex problem-solving.
Tools
read_graph
Read the entire knowledge graph
exa_answer
Ask a question and get a sourced answer via Exa /answer API.
upsert_entities
Create new entities or update existing ones in the knowledge graph using an upsert pattern
create_relations
Create multiple new relations between entities in the knowledge graph. Relations should be in active voice
add_observations
Add new observations to existing entities in the knowledge graph
delete_entities
Delete multiple entities and their associated relations from the knowledge graph
delete_observations
Delete specific observations from entities in the knowledge graph
delete_relations
Delete multiple relations from the knowledge graph
search_nodes
Search for nodes in the knowledge graph based on a query
open_nodes
Open specific nodes in the knowledge graph by their names
update_relations
Update multiple existing relations in the knowledge graph
memory_query
Query the memory store with advanced filters
think
Use the tool to think about something. It will not obtain new information or change the database, but just append the thought to the log. Use it when complex reasoning or some cache memory is needed. Consider including: problem definition, relevant context, analysis steps, self-reflection on your reasoning, and conclusions. Adapt this structure as needed for your specific thought process.
plan_tasks
Create multiple tasks from a plan. Generates IDs and syncs with knowledge graph.
list_tasks
List tasks with optional filtering by status and priority.
next_task
Get the next highest priority todo task and mark it as in-progress.
complete_task
Mark a task as completed.
update_tasks
Update multiple tasks with new values.
show_memory_path
Return absolute path of the active knowledge-graph file.
exa_search
Search the web using Exa API
README
推荐服务器
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。
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。
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。
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。
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。
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。
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。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
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。