
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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.