"Developing an application by analyzing specified development and API documentation" 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.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

MCP server enabling interaction with ServiceNow API for managing incidents, CMDB, change management, and other ServiceNow operations via natural language.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables users to track job and internship applications, statuses, deadlines, and interviews, with upcoming reminders and CSV or Markdown export. It runs locally and stores data in a single JSON file without network calls, accounts, or API keys.

An MCP server that talks directly to Jira Cloud REST API v3 using static credentials and exposes tools for discovering customfield IDs, resolving account IDs, and updating issue fields including ADF JSON.

Enables AI assistants to manage Tempo timesheets and perform write operations such as create, update, delete, submit, approve, reject, reopen, and recall, with user confirmation safeguards.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables AI clients to create and manage tasks via a local REST API by converting natural language into HTTP requests through the Model Context Protocol.

This read-only MCP Server allows you to connect to Jira data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

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

MCP server for Todoist API integration, allowing management of tasks, projects, sections, labels, and comments through natural language.

Enables AI assistants to read and manage YouGile boards, including projects, columns, tasks, and comments.

Enables interaction with XTRF translation management system through their Home Portal API. Provides access to XTRF's project management, translation workflow, and client portal functionalities via natural language interface.

Enables AI agents to track and manage product development projects through structured 7-phase lifecycles with sprint tracking, role-based collaboration, and multi-project support. Provides phase management, progress tracking, and team coordination tools for complete product development workflows.

Local-first shared memory that several AI apps can use at once, with every change recording which app, model and machine made it.

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.

Enables AI to read live weather data and manage a persistent to-do list through MCP tools, demonstrating both read and write capabilities without API keys.