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\n \n

\n The fastest way to build workflows with an AI agent platform!\n

\n \n $\"License\"$ \n |\n \n Docs\n |\n \n Homepage\n \n

\n\n# iFlytek Workflow MCP Server\n\n[The Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) is an open protocol designed for effortless integration between LLM applications and external data sources or tools, offering a standardized framework to seamlessly provide LLMs with the context they require.\n\nThis a simple implementation of an MCP server using iFlytek. It enables calling iFlytek workflows through MCP tools.\n\n## Features\n\n### Functional Overview\n\nThis system is built on the iFlytek MCP server and enables intelligent workflow scheduling, making it suitable for various business scenarios.\n\n- **Workflow Structure**: Composed of multiple nodes, supporting 14 types of nodes (including basic, tool, logic, and transformation types).\n- **Core Components**: By default, the workflow includes a **Start Node** (user input) and an **End Node** (output result).\n- **Execution Mode**: Once triggered, the workflow executes automatically according to predefined sequences and rules, requiring no manual intervention.\n\n### Core Capabilities\n\n#### **Robust Node Support**\n\n- 14 types of workflow nodes to meet diverse business requirements.\n- Supports **complex variable I/O**, enabling flexible data transmission.\n\n#### **Advanced Orchestration Modes**\n\n- **Sequential Execution**: Tasks execute one after another in order.\n- **Parallel Execution**: Multiple tasks run simultaneously to enhance efficiency.\n- **Loop Execution**: Supports iterative loops for handling repetitive tasks.\n- **Nested Execution**: Allows embedding sub-workflows within workflows, improving reusability.\n- Utilizes the **Hook Mechanism** to enable **streaming output**, ensuring real-time processing.\n\n#### **Multiple Development Paradigms**\n\n- **Single-turn, single-branch**: Linear execution of simple tasks.\n- **Single-turn, multi-branch**: Supports branching logic to handle complex processes.\n- **Single-turn loop**: Manages looped tasks to enhance automation.\n- **Multi-turn interaction**: Supports context memory for dynamic conversations.\n\n### Capability Expansion\n\n- **Multi-Model Support**: Based on the **Model of Models (MoM)** hybrid application architecture, providing multiple model choices at critical workflow stages. This allows for flexible model combinations, improving task adaptability.\n\n\n\n## Usage with MCP client\n\n### Prepare config.yaml\n\nBefore using the mcp server, you should prepare a config.yaml to save your workflow info. The example config like this:\n\n```yaml\n- flow_id: 'flow id' # required\n name: 'flow name' # optional, if not set, obtain the name from the cloud.\n description: 'flow description' # optional, if not set, obtain the description from the cloud.\n api_key: 'API Key:API Secret' # required\n```\n\n#### Get workflow authentication information\n1. [Create a bot](https://xinghuo.xfyun.cn/botcenter/createbot)\n![](./images/create_workflow.png)\n\n2. Publish a workflow\n- **Step 1.** Debug the workflow you just created.\n- **Step 2.** Engage in a conversation with your workflow and ensure the conversation is successful.\n- **Step 3.** You can now click the publish button.\n![](./images/debug_workflow.png)\n- **Step 4.** Select \"Publish as API\" and click the \"Configure\" button.\n![](./images/publish_workflow.png)\n- **Step 5.** Select the application you need to bind and bind it. Now you can retrieve the corresponding workflow ID and authentication information. Enjoy!\n![](./images/bind_app.png)\n> **Note**: If you find that you are unable to select an app, you can go to https://www.xfyun.cn to apply.\n### Manual Installation\n\nTo add a persistent client, add the following to your `claude_desktop_config.json` or `mcp.json` file:\n\n```json\n{\n \"mcpServers\": {\n \"ifly-workflow-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"--from\",\n \"git+https://github.com/iflytek/ifly-workflow-mcp-server\",\n \"ifly_workflow_mcp_server\"\n ],\n \"env\": {\n \"CONFIG_PATH\": \"$CONFIG_PATH\"\n }\n }\n }\n}\n```\n\n\n\nExample config:\n\n```json\n{\n \"mcpServers\": {\n \"ifly-workflow-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"--from\",\n \"git+https://github.com/iflytek/ifly-workflow-mcp-server\",\n \"ifly_workflow_mcp_server\"\n ],\n \"env\": {\n \"CONFIG_PATH\": \"/Users/hygao1024/Projects/config.yaml\"\n }\n }\n }\n}\n```\n\n\n","url","https://github.com/iflytek/ifly-workflow-mcp-server","githubRepository",{"_64":65,"_66":67,"_68":69,"_70":71,"_72":73,"_74":75,"_79":80,"_81":82,"_84":80},"defaultBranch","main","fullName","iflytek/ifly-workflow-mcp-server","githubTreeId",103455,"language","Python","name","ifly-workflow-mcp-server","owner",{"_76":77,"_17":78},"login","iflytek","sAE1BGuo5z","recentStargazers",2,"spdxLicense",{"_72":83},"MIT License","stargazers","glamaJson","id",3753,"inspectable","integrations",[],"iFlytek Workflow MCP Server","namespace","npmPackage","prompts","redditPostForeignId","relatedMcpServerIds",[98,99,100,101,102,103],596,2648,2690,1624,1681,1343,"resources","scores",{"_107":108,"_109":-5,"_110":-5},"license",100,"quality","security","simpleIcon","slug","supportedPlatforms",[115,116],"WINDOWS","MACOS","tools","7yl55r9ix4","updatedAt",["D",1742979641911],"meta",[123,126,128,135,138,140,143,146,149,152,155,157,160,163,165,167,169,171,173],{"_124":125},"title","iFlytek Workflow MCP Server | Glama",{"_127":54,"_72":39},"content",{"_129":130,"_131":132,"_133":134},"href","https://glama.ai/mcp/servers/@iflytek/ifly-workflow-mcp-server","rel","canonical","tagName","link",{"_127":91,"_136":137},"property","og:title",{"_127":54,"_136":139},"og:description",{"_127":141,"_136":142},"https://glama.ai/logo.png","og:logo",{"_127":144,"_136":145},"https://glama.ai/mcp/servers/@iflytek/ifly-workflow-mcp-server/og-image","og:image",{"_127":147,"_136":148},"630","og:image:height",{"_127":150,"_136":151},"1200","og:image:width",{"_127":153,"_136":154},"website","og:type",{"_127":130,"_136":156},"og:url",{"_127":158,"_136":159},"ChatGPT alternative for power users","og:site_name",{"_127":161,"_72":162},"summary_large_image","twitter:card",{"_127":158,"_72":164},"twitter:title",{"_127":54,"_72":166},"twitter:description",{"_127":144,"_72":168},"twitter:image",{"_127":147,"_72":170},"twitter:image:height",{"_127":150,"_72":172},"twitter:image:width",{"_174":175},"script:ld+json",{"_176":177,"_178":179},"@context","http://schema.org","@graph",[180],{"_176":181,"_182":183,"_184":185},"https://schema.org","@type","BreadcrumbList","itemListElement",[186,193,196,200],{"_182":187,"_188":189,"_72":190,"_191":192},"ListItem","item","https://glama.ai/","Glama","position",1,{"_182":187,"_188":194,"_72":195,"_191":80},"https://glama.ai/mcp","MCP",{"_182":187,"_188":197,"_72":198,"_191":199},"https://glama.ai/mcp/servers","Servers",3,{"_182":187,"_188":130,"_72":91,"_191":201},4,"routes/_public/mcp/servers/~namespace/~slug/_pages/_explorer/blob/~branch/~/_route",{"_204":205,"_209":65,"_29":210,"_226":227,"_228":229},"blob",{"_127":206,"_207":208},"# Python-generated files\n__pycache__/\n*.py[oc]\nbuild/\ndist/\nwheels/\n*.egg-info\n\n# Virtual environments\n.venv\n\n# custom\n.vscode\nconfig.yaml\n.idea","fileName",".gitignore","branch",{"_31":211,"_33":212,"_13":216,"_53":54,"_55":54,"_56":217,"_62":218,"_85":-5,"_86":87,"_88":28,"_89":221,"_72":91,"_92":77,"_93":-5,"_94":-5,"_95":-5,"_96":222,"_104":-5,"_105":223,"_111":-5,"_112":73,"_113":224,"_117":-5,"_17":118,"_119":225},["D",1742930822423],{"_35":213,"_43":215,"_41":45},{"_37":214},{"_39":40,"_41":42},[37],[47,48,49,50,51,52],{"_58":59,"_60":61},{"_64":65,"_66":67,"_68":69,"_70":71,"_72":73,"_74":219,"_79":80,"_81":220,"_84":80},{"_76":77,"_17":78},{"_72":83},[],[98,99,100,101,102,103],{"_107":108,"_109":-5,"_110":-5},[115,116],["D",1742979641911],"path","","treeMembers",[230,233,235,236,238,240,242,244,246],{"_226":231,"_41":232},"images","tree",{"_226":234,"_41":232},"src",{"_226":208,"_41":204},{"_226":237,"_41":204},"LICENSE",{"_226":239,"_41":204},"poetry.lock",{"_226":241,"_41":204},"pyproject.toml",{"_226":243,"_41":204},".python-version",{"_226":245,"_41":204},"README.md",{"_226":247,"_41":204},"uv.lock","actionData","errors"]