Agentic Tools MCP Server: an MCP server for agentic AI tools offering AI project management, AI task management, and pro
Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
Google Workspace MCP
Control Gmail, Google Calendar, Docs, Sheets, Slides, Chat, Forms, Tasks, Search, and Drive with AI. Comprehensive Googl
Arize Phoenix
Arize Phoenix — unified interface for managing prompts, exploring datasets, and running LLM experiments across providers
Octocode
Octocode seamlessly integrates with GitHub CLI and npm for fast code discovery, repo analysis, and commit tracking with
Context Portal
Context Portal: Manage project memory with a database-backed system for decisions, tracking, and semantic search via a k
Genkit
Genkit — consume MCP resources or expose powerful Genkit tools as a server for streamlined development and integration.
Agentic Tools MCP Server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Agentic Tools MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, Agentic Tools MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Agentic Tools MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Agentic Tools MCP Server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We evaluated Agentic Tools MCP Server against two servers with overlapping tools; this profile had the clearer scope statement.
Agentic Tools MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Useful MCP listing: Agentic Tools MCP Server is the kind of server we cite when onboarding engineers to host + tool permissions.
Agentic Tools MCP Server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Agentic Tools MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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Claude Desktop configuration
{
"mcpServers": {
"agentic-tools": {
"command": "npx",
"args": [
"-y",
"@pimzino/agentic-tools-mcp"
]
}
}
}Provides AI assistants with comprehensive project and task management capabilities, including unlimited task nesting, time tracking, and project-specific storage.
Agentic Tools MCP Server is a community-built MCP server published by Pimzino that provides AI assistants with tools and capabilities via the Model Context Protocol. Agentic Tools MCP Server: an MCP server for agentic AI tools offering AI project management, AI task management, and pro It is categorized under ai ml, productivity.
You can install Agentic Tools MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
A comprehensive Model Context Protocol (MCP) server providing AI assistants with powerful advanced task management and agent memories capabilities with project-specific storage.
This MCP server is part of a complete task and memory management ecosystem:
💡 Pro Tip: Use both together for the ultimate productivity experience! The VS Code extension provides a visual interface while the MCP server enables AI assistant integration with advanced features like PRD parsing, task recommendations, and research capabilities.
parentId fieldlist_projects - View all projects in a working directorycreate_project - Create a new project in a working directoryget_project - Get detailed project informationupdate_project - Edit project name/descriptiondelete_project - Delete project and all associated datalist_tasks - View tasks in hierarchical tree format with unlimited depth visualizationcreate_task - Create tasks at any hierarchy level with parentId (supports unlimited nesting)get_task - Get detailed task information including hierarchy relationshipsupdate_task - Edit tasks, metadata, or move between hierarchy levels with parentIddelete_task - Delete task and all child tasks recursivelymove_task - Dedicated tool for moving tasks within hierarchy structuremigrate_subtasks - Automatic migration tool for converting legacy subtasks to unified modelparse_prd - Parse Product Requirements Documents and automatically generate structured tasksget_next_task_recommendation - Get intelligent task recommendations based on dependencies, priorities, and complexityanalyze_task_complexity - Analyze task complexity and suggest breaking down overly complex tasksinfer_task_progress - Analyze codebase to infer task completion status from implementation evidenceresearch_task - Guide AI agents to perform comprehensive web research with memory integrationgenerate_research_queries - Generate intelligent, targeted web search queries for task researchlist_subtasks - View child tasks (legacy compatibility, now uses unified Task model)create_subtask - Create child tasks (legacy compatibility, creates tasks with parentId)get_subtask - Get task information (legacy compatibility for existing subtasks)update_subtask - Edit child tasks (legacy compatibility, uses unified Task operations)delete_subtask - Delete child tasks (legacy compatibility, deletes tasks recursively)create_memory - Store new memories with title and detailed contentsearch_memories - Find memories using intelligent multi-field search with relevance scoringget_memory - Get detailed memory informationlist_memories - List memories with optional filteringupdate_memory - Edit memory title, content, metadata, or categorizationdelete_memory - Delete a memory (requires confirmation)Important: All tools require a workingDirectory parameter to specify where the data should be stored. This enables project-specific task and memory management.
npx -y @pimzino/agentic-tools-mcp
npm install -g @pimzino/agentic-tools-mcp
The MCP server supports two storage modes:
Data is stored in .agentic-tools-mcp/ subdirectories within each project's working directory.
npx -y @pimzino/agentic-tools-mcp
Use the --claude flag to store all data in a standardized global directory:
C:\Users\{username}\.agentic-tools-mcp\~/.agentic-tools-mcp/npx -y @pimzino/agentic-tools-mcp --claude
When to use --claude flag:
Note: When using --claude flag, the workingDirectory parameter in all tools is ignored and the global directory is used instead.
{
"mcpServers": {
"agentic-tools": {
"command": "npx",
"args": ["-y", "@pimzino/agentic-tools-mcp"]
}
}
}
{
"mcpServers": {
"agentic-tools": {
"command": "npx",
"args": ["-y", "@pimzino/agentic-tools-mcp", "--claude"]
}
}
}
Note: The server now includes both task management and agent memories features.
agentic-toolsnpx -y @pimzino/agentic-tools-mcpagentic-toolsnpx -y @pimzino/agentic-tools-mcp --claudeFeatures Available: Task management, agent memories, and text-based search capabilities.
For the best user experience, install the Agentic Tools MCP Companion VS Code extension:
F5 to run in development modeBenefits of using both together:
The server uses STDIO transport and can be integrated with any MCP-compatible client:
npx -y @pimzino/agentic-tools-mcp
npx -y @pimzino/agentic-tools-mcp --claude
{
id: string; // Unique identifier
name: string; // Project name
description: string; // Project overview
createdAt: string; // ISO timestamp
updatedAt: string; // ISO timestamp
}
{
id: string; // Unique identifier
name: string; // Task name
details: string; // Enhanced description
projectId: string; // Parent project referenc
---
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.