"Workflow builder and monitoring tools" matching MCP servers:

A Model Context Protocol server that exposes AI workflow templates as callable tools, enabling MCP clients to list templates, inspect their input/output schemas, and execute them synchronously or asynchronously to get structured results.

A standalone runtime and MCP server that executes Claude Code dynamic workflow files through interchangeable agent providers, ensuring compatibility with Claude Code's workflow format.

Enables multi-agent code review and iterative improvement loop using different LLM backends, with deterministic scoring and audit trail.

Enables AI agents to create, share, discover, and execute reusable multi-step workflow templates.

A production-grade multi-agent workflow orchestrator built on the Model Context Protocol, featuring planner/executor/critic agents, durable run state, and replayable traces.

Orchestrates multiple MCP tool calls into sequential workflows with conditional logic, data transformation via JSONPath, and workflow templates.

Enables enterprise multi-agent decision workflows that expose 8+ MCP tools such as SQL query, web search, Python sandbox, RAG, file access, data cleaning, chart generation, and HTTP calls, orchestrated with LangGraph, streaming output, and human-in-the-loop approvals.

Guides AI agents through structured, multi-step workflows with discovery, navigation, and fidelity enforcement.

Enables deterministic, step-by-step execution of YAML-defined skills and workflows for AI agents, with progressive disclosure of active-step instructions and tools. It manages workflow state, conditional DAG transitions, loops, and persistent sessions via start_workflow, next_step, and end_workflow.

Provisions isolated SAP SuccessFactors demo orgs and generates two-surface demo scripts for Joule Chat and Joule Desktop/Claude Code.

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

A server implementation of the Model Context Protocol that enables calling iFlytek workflows, supporting complex orchestration modes like sequential, parallel, and looped execution across 14 node types for diverse business scenarios.

A passive MCP server that exposes a toolbox of executable tools (shell, network, HTTP, AI search, SSH, S3 file operations) to autonomous agents via Streamable HTTP, with strong security features including Docker sandboxing and WAF.

Transforms any API into an intelligent MCP agent in seconds, enabling natural language interaction with APIs through the Model Context Protocol.

Enables approval-gated incident response workflows that gather evidence through read-only MCP tools, perform idempotent writes, and preserve a durable audit trail.

An MCP (Model Context Protocol) server implementation using HTTP SSE (Server-Sent Events) connections with built-in utility tools including echo, time, calculator, and weather query functionality.

A Python-based MCP server that provides coordinate conversion between latitude/longitude and UTM/TWD97, along with various civil engineering calculation tools for LLM and AI application integration.

An MCP server that exposes 43 domain tools behind 4 meta-tools, applying guardrails such as budgets, rate limits, schema validation, human-in-the-loop confirmation for mutations, PII redaction, and an append-only audit log while reducing context window usage.

Sub-15ms edge intelligence tools for Claude Desktop, Cursor, and LLM agent loops. Provides sub-millisecond LLM JSON repair, web-to-markdown token compression (cuts context tokens up to 90%), PII redaction, and RFC 5322 B2B email deliverability verification at zero marginal token cost.

Enables web ChatGPT to drive durable, sandboxed Claude Code sessions on a local Mac, with controlled read, modify, verify, and recover operations via six session control tools.