"Connecting Firebase to a data source or application" matching MCP servers:

Enables AI agents to manage job applications, documents, and contacts via the Application Tracker workspace, with read-only or write access controlled by administrator settings.

A privacy-first MCP server for locally managing job, fellowship, and graduate-school applications. It offers tools for tracking application status, analyzing role fit, generating LaTeX CV/cover letters, interview prep, and discovering public jobs from ATS APIs.

Enables Claude Web users to manage their job application workflow by storing profile and resume data, analyzing job descriptions, preparing applications, and tracking progress — all with manual submission and no platform automation.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Enables agentic co-authoring of feature specs, decomposition into architecture-validated tickets, and idempotent syncing to Linear as projects with epics, sub-issues, and dependencies.

Enables AI clients like Claude to read and manage Microsoft To Do task lists and tasks via the Microsoft Graph API, running locally over stdio with secure token storage.

Enables AI assistants to manage todo lists through natural language by creating, listing, updating, completing, and deleting tasks stored in Firebase Firestore. Supports custom system prompts for personalized task management workflows.

Enables managing Microsoft To Do lists and tasks through MCP, including creating, updating, completing, deleting, searching, and checklist operations via Microsoft Graph.

Enables to manage to-do items through natural language, with tools for creating, reading, updating, and deleting tasks.

A Model Context Protocol (MCP) server that connects AI assistants to Jira Server/Data Center, enabling issue management, JQL search, sprint tracking, and natural language interaction with Jira.

Automates job application tracking and resume/cover letter generation using AI, integrating with Google Drive, Notion, and Gmail.

AI job search and job application tracker. Search live jobs by title, location, salary, date posted, and remote or on-site, and see each one checked on real data: pay against market rates, ghost-job signals, visa sponsorship history, and how well it matches your resume. Check how hiring software reads your resume, track applications, set follow-up reminders, and get email alerts.

Lets Claude and other AI clients read and modify Microsoft To Do through natural language, adding, completing, searching, updating, and deleting tasks and sub-steps by title and list name instead of ids. Personal Microsoft accounts need no Azure app registration — a single device-code sign-in grants access, with optional read-only and no-delete modes available.

A Python MCP server that retrieves requirements and bug data from TAPD platform to provide AI clients with project management information.

Enables OAuth-capable MCP clients to connect to personal Microsoft To Do accounts and read lists, create or update tasks, manage checklist items, set due dates, and complete tasks.

MCP server for Redmine that enables interaction with issues, wiki pages, and time entries through natural language.

Enables coding agents to manage Microsoft To Do lists and tasks through Microsoft Graph, with optional support for checklist items, linked resources, attachments, and delta synchronization.

A Model Context Protocol (MCP) server that enables AI assistants like Claude and Cursor to interact with Microsoft To Do via the Microsoft Graph API.

Enables Claude to create, read, update and delete Microsoft To Do lists, tasks and checklist items, and Microsoft Planner plans, buckets and tasks, through Microsoft Graph as the signed-in user. Lists, plans and buckets can be referenced by ID or exact name, with destructive deletes requiring confirmation.

Enables an AI assistant to manage a simple to-do list stored in a local JSON file, with tools to add, list, get, complete, and delete tasks, plus a read-only pending tasks resource.