"A service for data access, task automation, file management, and API integration" matching MCP servers:

Self-hosted credential store and API proxy for AI agents. One Bearer token, all your services. Handles OAuth refresh, encrypted storage, audit logging, and per-agent permissioning.

A persistent 24/7 background daemon that aggregates all downstream MCP servers into one unified connection and layers on a real-time notification gateway so AI agents can receive events from X/Twitter, Slack, Email, and webhooks.

Exposes enterprise tools to third-party AI agents through a single guard that authorizes each call against default-deny, purpose-scoped entitlements, executes it, and writes a hash-chained, tamper-evident decision trace the firm owns. It also verifies signed vendor webhooks and enforces a strict versioned contract, so agent activity stays scoped, auditable, and portable across vendors.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

A Model Context Protocol service that enables agent authentication and integration with TrustGo platform, providing access to real-time data like price, sigma score, and mindshare bubble analytics.

Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.

Proxies a remote MCP server to add protocol-native background task support, including task management and progress forwarding, while preserving synchronous calls.

An MCP Server providing access to Google's Firebase API, allowing natural language interaction with Firebase services and resources.

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

An MCP server for task orchestration.

Enables AI agents to manage live Firefox tabs and native tab groups via MCP tools over stdio, with exact-match verification and safety constraints. It does not read page content or send browser data remotely.

This MCP server enables agents to manage complex tasks by providing tools for registration, complexity assessment, breakdown into subtasks, and status tracking throughout the task lifecycle.

Enables agents to select the provably optimal set of candidate actions under a budget, with optional conflicts and prerequisites, and to re-plan to the single best next action after each outcome. Also validates any proposed selection for feasibility.

Enables AI agents to report task lifecycle events—start, progress, waiting, rename, and terminal outcomes—so a single Huawei Today screen card stays updated per task under one task_id. Delivers these notifications through a self-hosted Cloudflare Workers deployment with OAuth-scoped agents, queued retries, and an admin console for notification policies.

Provides tools for coordinating AI agent work on one machine through a local SQLite-backed queue and kanban, including task creation, atomic claiming, lease renewal, completion/failure, listing, comments, and cancellation.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables Codex to spawn, monitor, send messages to, and list DSH background tasks via a local REST bridge, wrapping six task-coordination endpoints as MCP tools.

Provides structured workflows (phases, gates, coordination) for AI agents, enabling complex task execution with quality enforcement and multi-agent coordination via Model Context Protocol.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

Enables ChatGPT to inspect Jobber data and manage controlled automations with scheduling, approval workflows, and audit trails.

Enables MCP clients to run complete browser workflows through a single run_workflow tool, with anti-detection backends, intelligent element location, automatic retries, and session persistence.

Enables AI coding agents from different MCP-capable clients to exchange messages in real time through a shared in-memory broker. Supports agent registration, inboxes, and live event streaming without requiring a database.

Enables creation and management of scheduled tasks with interval, cron, or one-time triggers. Persists tasks in SQLite and supports MCP sampling to automatically invoke AI agents when schedules trigger.

Exposes an agent orchestration task queue as an MCP tool interface, allowing agents to submit, list, get, and update tasks with typed validation.

An MCP server that integrates with AI editors like Cursor to maximize agentic capabilities while solving context window limitations, providing a Svelte UI for task planning and implementation tracking.

Enables reviewing and dispatching existing Codex tasks across projects through a lightweight control panel, including scanning task inventories, confirming Continue or Optimize prompts, and tracking dispatch progress.

Enables AI agents to run durable, isolated, and observable browser automation tasks via Playwright, with persistent profiles, recovery, evidence capture, and unattended execution for long-running web workflows.

Provides a self-hosted shared work queue for AI agents via MCP, using a local SQLite database for task management.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.