HAP-MCP
MCP ServerFree** - HAP (Super Application Platform) is developed by Mingdao（ https://www.mingdao.com ）The launched APaaS platform helps you build enterprise level applications quickly without coding. This is HAP's MCP (Model Context Protocol) server, used for seamless integration of AI. It enables every zero code
Capabilities9 decomposed
zero-code application exposure as mcp tools
Medium confidenceAutomatically exposes HAP-built no-code applications as Model Context Protocol (MCP) tools that AI agents can discover and invoke. The MCP server acts as a bridge layer that introspects HAP application schemas (workflows, data models, API endpoints) and translates them into standardized MCP tool definitions with proper input/output schemas, enabling agents to treat low-code applications as native capabilities without custom integration code.
Bridges the no-code/AI divide by automatically converting HAP application capabilities into MCP-compliant tools without requiring developers to manually define schemas or integration logic — the MCP server acts as a dynamic adapter layer that introspects HAP's application structure at runtime
Unlike manual MCP tool definition or REST-to-MCP adapters, HAP-MCP leverages the platform's native schema awareness to automatically expose zero-code applications as first-class agent tools, eliminating integration boilerplate
hap workflow invocation through agent function calls
Medium confidenceEnables AI agents to trigger HAP workflows and business processes by calling them as functions through the MCP protocol. The MCP server translates agent function calls into HAP API requests, manages parameter mapping between agent outputs and HAP input schemas, handles asynchronous workflow execution, and returns results back to the agent's reasoning context. Supports both synchronous (blocking) and asynchronous (fire-and-forget) invocation patterns.
Implements bidirectional parameter mapping and execution context management between MCP function calls and HAP workflows, including support for both blocking and non-blocking invocation patterns — the server handles the impedance mismatch between agent reasoning (stateless, synchronous) and HAP workflow execution (stateful, potentially long-running)
More tightly integrated than generic REST-to-MCP adapters because it understands HAP's workflow semantics and can map agent outputs directly to HAP input schemas, reducing the need for intermediate transformation logic
hap data model querying and retrieval via agent context
Medium confidenceAllows AI agents to query and retrieve data from HAP data models (tables, collections) through MCP tool definitions, enabling agents to access enterprise data as part of their reasoning. The MCP server translates agent query intents into HAP API calls, handles filtering/sorting/pagination parameters, and returns structured data that agents can reason over. Supports both simple lookups and complex filtered queries.
Exposes HAP data models as queryable MCP tools with schema-aware filtering and pagination, allowing agents to treat enterprise data as first-class context rather than requiring separate API calls — the server handles the translation between agent query intent and HAP's query API
More integrated than generic database query tools because it understands HAP's data model structure and can automatically generate appropriate query tools with proper schema validation
hap api endpoint exposure as mcp resources
Medium confidenceExposes HAP's REST API endpoints as MCP resources that agents can discover and invoke. The MCP server introspects HAP's API documentation or OpenAPI schema, translates endpoints into MCP resource definitions with proper HTTP method mapping, parameter handling, and response parsing. Agents can then call these endpoints through the MCP protocol without needing to know the underlying REST API structure.
Automatically translates HAP's REST API surface into MCP-compliant resource definitions with proper HTTP semantics preservation, enabling agents to invoke APIs through a unified protocol without REST-specific knowledge
More seamless than manual REST client integration because it leverages HAP's API schema to auto-generate MCP resources, reducing boilerplate and keeping resource definitions in sync with API changes
agent-driven hap application state mutation and updates
Medium confidenceEnables AI agents to create, update, and delete records in HAP data models through MCP function calls. The MCP server translates agent mutation intents into HAP API write operations, validates input data against HAP schemas, handles transaction semantics, and returns confirmation/results. Supports both single-record and batch operations with rollback capabilities.
Implements schema-aware validation and transaction handling for agent-driven mutations, ensuring data consistency when agents modify HAP records — the server acts as a guard layer that validates agent outputs against HAP schemas before committing changes
More robust than direct API calls because it validates mutations against HAP schemas before execution and provides structured error feedback, reducing the risk of agents creating invalid data
mcp server lifecycle management and hap connection pooling
Medium confidenceManages the MCP server's connection to HAP instances, including authentication, connection pooling, credential rotation, and graceful shutdown. The server maintains persistent connections to HAP APIs, reuses connections across multiple agent requests, handles authentication token refresh, and implements health checks to detect connection failures. Supports multiple HAP instance configurations for multi-tenant scenarios.
Implements connection pooling and credential management specifically for HAP's API patterns, reducing per-request overhead and enabling long-lived agent sessions without authentication failures
More efficient than creating new HAP connections per agent request because it maintains a pool of reusable connections and handles credential rotation transparently
agent error handling and hap failure recovery
Medium confidenceImplements error handling and recovery strategies for agent interactions with HAP, including retry logic for transient failures, circuit breakers for cascading failures, timeout management, and structured error reporting. The MCP server catches HAP API errors, classifies them (transient vs permanent), applies appropriate recovery strategies, and returns actionable error information to agents for decision-making.
Implements HAP-aware error classification and recovery strategies that distinguish between transient API failures (rate limits, timeouts) and permanent failures (invalid requests, authentication), applying appropriate recovery logic for each
More sophisticated than generic HTTP error handling because it understands HAP's specific error patterns and applies domain-appropriate recovery strategies
multi-agent concurrent request handling and rate limiting
Medium confidenceManages concurrent requests from multiple AI agents to HAP through the MCP server, implementing request queuing, rate limiting, and fair scheduling. The server enforces HAP API rate limits, prevents agent requests from overwhelming the platform, implements backpressure mechanisms, and ensures fair resource allocation across agents. Supports both per-agent and global rate limit configurations.
Implements HAP-aware rate limiting that understands the platform's specific API quotas and applies fair scheduling across multiple agents, preventing any single agent from monopolizing HAP resources
More effective than agent-side rate limiting because it enforces limits at the MCP server layer where all agent requests converge, ensuring global fairness and preventing HAP overload
hap workflow schema introspection and mcp tool generation
Medium confidenceAutomatically introspects HAP workflow definitions and generates corresponding MCP tool schemas that agents can discover and invoke. The MCP server queries HAP's workflow metadata, extracts input/output specifications, generates JSON schemas for MCP tool definitions, and keeps them synchronized with HAP changes. Supports dynamic tool discovery so agents can access newly created workflows without server restart.
Implements runtime schema introspection that automatically generates MCP tool definitions from HAP workflow metadata, enabling agents to discover and invoke workflows without manual tool definition — the server acts as a dynamic adapter that keeps tool schemas synchronized with HAP changes
More maintainable than manually defining MCP tools for each HAP workflow because schema changes in HAP automatically propagate to agents without requiring MCP server updates
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓Enterprise teams using HAP APaaS platform who want AI agent integration
- ✓No-code builders extending applications with AI capabilities
- ✓Organizations building multi-agent systems that need to orchestrate HAP workflows
- ✓Developers building AI agents that orchestrate enterprise workflows
- ✓Teams automating multi-step business processes that span no-code and AI logic
- ✓Organizations using HAP for process automation who want AI-driven decision making
- ✓Developers building AI agents that need access to enterprise data in HAP
- ✓Teams using HAP as a data layer for agent-driven applications
Known Limitations
- ⚠Requires HAP instance with exposed APIs or webhooks — cannot introspect closed/private applications
- ⚠Schema translation latency depends on HAP application complexity; deeply nested workflows may produce large MCP tool definitions
- ⚠Limited to HAP's native capability set — cannot expose custom JavaScript/Python extensions unless HAP exposes them via API
- ⚠No built-in caching of schema definitions — each agent connection may re-introspect application structure
- ⚠Workflow execution timeout depends on HAP configuration — long-running workflows may exceed agent context windows
- ⚠Parameter type coercion between agent outputs (typically strings/JSON) and HAP input types may fail silently if schemas don't align
Requirements
Input / Output
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About
** - HAP (Super Application Platform) is developed by Mingdao（ https://www.mingdao.com ）The launched APaaS platform helps you build enterprise level applications quickly without coding. This is HAP's MCP (Model Context Protocol) server, used for seamless integration of AI. It enables every zero code application built through HAP to quickly become a tool for agents.
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