"An example MCP for client prototyping in a business context with a public API call" matching MCP servers:

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

MCP server for the Plane project management API, enabling issue retrieval, listing, commenting, state changes, and creation.

Enables the creation and management of business design artifacts including Business Model Canvases, SWOT analyses, and user personas. It features project organization and AI-powered research tools to automatically populate frameworks with market data.

A local, provider-neutral MCP server for repository-scoped issue handling. It provides a guarded interface to Linear, GitHub Issues, GitHub Projects v2, and Jira Cloud, with preview/apply safety and host-local configuration.

Example MCP server for Autodesk Platform Services that demonstrates proper OAuth authorization with Auth0 as the first layer and APS 3-legged OAuth as the second layer. Enables querying APS projects and issues through natural language after authenticating via Auth0 and APS.

Enables task management through MCP tools, resources, and prompts, backed by a PostgreSQL database.

An MCP server that gives LLMs read-only access to Microsoft Project Online (Project for the Web) via the Microsoft Graph API.

An MCP server exposing internal business operations as tools — task management (create, list, update status) and RAG-style semantic search over an internal knowledge base (leave, expense, and onboarding policies) that any MCP-compatible AI agent can call directly for grounded, non-hallucinated answers.

Enables MCP-compatible coding agents to share persistent project context, task claims, handoffs, decisions, test reports, and searchable history through a local or team-hosted SQLite-backed service with a React dashboard.

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.

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

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

Enables AI clients to locally store and share tasks, work activities, long-term memory, knowledge, and people information, while allowing users to review saved content and generate briefings or reports through a web UI.

Fetches structured Jira issue context from a URL, enabling coding agents to quickly understand issue intent and implementation details.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

Enables Boneyard to call authenticated, stateless Streamable HTTP tools for searching tickets and adding ticket comments, with caller context, attribution, and bounded results.

A local-first MCP server and CLI that gives coding agents structured project memory, task contracts, context packs, backlog workflows, and verification evidence, storing data in reviewable Markdown/YAML with a fast SQLite index.

Read-only MCP server that fetches a single Jira issue by key and returns its title, description, comments, attachment summary, and image attachments.

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 assistants to manage Bitrix24 CRM entities, tasks, project kanban boards, and Scrum sprints through an incoming webhook, requiring explicit user confirmation for all write operations.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Enables Codex projects to read Git-backed kickoff, acceptance, handoff, progress, and next-step context, and to append validated, audited progress events through scoped MCP tools. This supports visible agent progress, resumable sessions, and safer handoffs.

Enables Codex and other MCP clients to read kickoff cards, acceptance criteria, Git evidence, and next steps, then append validated, audited progress events for resumable project handoffs.

Enables AI-powered project management by connecting Claude to Planka kanban boards via 75+ MCP tools for creating, updating, and managing projects, boards, lists, and cards.

Enables agents to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited progress events with matching Git commits through short-lived scoped credentials.

Enables AI agents to retrieve Git-backed project context, handoff packages, progress, and next steps, and to append validated progress events with matching project-record commits. This supports visible agent progress, resumable work, and safe handoffs while keeping high-risk actions outside the MCP surface.

Enables agents to read Git-backed project context and append audited, idempotent progress events through scoped, short-lived credentials, supporting resumable handoffs and visible project state.

Enables AI agents and users to verify claims about Jira issues and issue counts against live Jira, retrieve verifiable facts for drafting updates, and re-check previously posted claims. It provides read-only tools and an issue panel so status updates can be evidence-based and mismatches corrected before or after posting.

Enables Codex sessions to read a project's kickoff card, acceptance criteria, handoff package, progress, Git trail, and next step, then append validated, idempotent progress events backed by matching project-record Git commits. Access is limited to a short-lived, revocable credential scoped to one workspace and project, with high-risk actions kept outside the server.