"Dapr" matching MCP servers:

Enables AI agents to look up and text-search Danish addresses, access addresses, streets, postcodes and cadastral parcels from the national address register, with DAR UUIDs, status codes and WGS84 coordinates. Includes raw GraphQL passthrough and schema retrieval for the keyed Datafordeleren service.

Enables coding agents to connect to Debug Adapter Protocol debuggers over MCP, allowing them to launch or attach to native targets, control execution, set breakpoints and watchpoints, inspect stacks, variables, memory, and exceptions, and capture agent-friendly debugger snapshots.

An MCP server that exposes Python debugging tools backed by debugpy, providing a focused debugging surface for local scripts.

Enables any MCP client to debug programs through the Debug Adapter Protocol, supporting launch/attach, breakpoints, stepping, variable inspection, evaluation, and memory operations via a single debug tool.

A Model Context Protocol server that bridges MCP and the Debug Adapter Protocol, enabling AI coding agents to launch and control debug sessions, set breakpoints, step through code, and inspect variables.

Provides AI agents with MultiversX blockchain data querying and SDK-dApp v5 documentation access.

Enables read-only search and retrieval of Korean defense acquisition statutes, administrative rules, precedents, and DAPA organizational/policy knowledge, with source verification and citation checking.

Provides AI agents with direct access to FileMaker databases through the FileMaker Data API, enabling natural language interactions for querying, managing records, and database introspection.

Enables controlling and inspecting a running Dolphin emulator through its Debug Adapter Protocol, with persistent connections, task-oriented tools, and a raw request escape hatch for execution, breakpoints, stack/variables, memory, disassembly, sources, watches, scans, and code injection.

Provides a Model Context Protocol interface for secure, multi-agent collaboration on Git repositories, offering isolated workspaces, change requests, reviews, and approval workflows with Git as the source of truth.

Enables safe, human-in-the-loop AI document collaboration by letting agents create isolated workspaces, edit tracked files, open reviewable Change Requests, and get human approval before merging, with Git-backed conflict detection and resolution.