"Access private Notion pages after logging in" matching MCP servers:

A Model Context Protocol (MCP) server for Adobe After Effects that enables AI assistants and other applications to control After Effects through a standardized protocol.

Persistent memory and pattern learning for AI coding assistants via MCP.

An auto-generated MCP server for Google's Serverless VPC Access API, enabling communication with Google Cloud VPC networks through natural language interactions.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Gives AI assistants full control over Microsoft Access databases, enabling creation and management of forms, VBA, tables, queries, and more through natural language.

Enables MCP clients like Claude Code to delegate coding tasks to the local Cursor Agent CLI, with persistent per-workspace sessions that resume across calls.

Wraps Claude Code as a server using the Model Context Protocol (MCP), allowing teams to interact with Claude Code through a Slack bot interface.

Ephemeral MicroVM-isolated code execution for AI agents. Run Python, Node, or bash — fresh hardware-isolated VM per call, hard-purged after. No state persists between calls.

Executes IDAPython scripts in IDA Pro through any MCP-compatible AI assistant, enabling AI-powered binary analysis with full access to IDA's API.

Enables running code against tests in an isolated sandbox to obtain PASS/FAIL verdicts with signed, offline-checkable certificates, and generating verified code with attached certificates after execution against derived tests.

Lightweight MCP server for After Effects that enables Cursor Agent to execute ExtendScript code inside AE via a single tool, similar to Blender MCP.

Enables AI assistants to write and debug integration tests by providing live access to DOM structure and executing code directly in test environments.

Runs AI-generated code in secure Firecracker microVMs with opt-in network policy enforcement, PII scanning, prompt injection defense, and audit logging. Exposes MCP tools for running commands, managing files, and the full sandbox lifecycle.

Enables coding assistants to access Perplexity AI for quick fact-checking and in-depth research. Provides two tools: lookup for fast documentation queries and answer for comprehensive research with recommendations.

Sandboxed bash execution MCP server for AI agents, using an in-memory virtual filesystem overlay to prevent real filesystem damage, with configurable network access, timeouts, and optional Python/JS runtimes.

Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.

Enables MCP-compatible AI agents to access Polymarket prediction-market data and run Python 3.12 in an isolated sandbox, with each call paid automatically in USDC on Base.

MCP server for executing shell commands with automatic RTK token reduction, persistent caching, and execution logging.

Allows AI assistants to access prompts from promptz.dev API without copy-pasting, reducing context switching in your development workflow.

Enables AI models to interact with AWS Lambda functions via the MCP protocol, allowing access to private resources, real-time data, and custom computation in a secure environment.