spring-ai-mcp: Java SDK for the Model Context Protocol, providing seamless integration between Java and Spring applications

Last updated: 2025-02-14 · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 76/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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Quick Facts

Stars	204
Forks	50
Language	Java
Category	MCP Server
License	Apache-2.0
Quality Score	76/100
Open Issues	5
Last Updated	2025-02-14
Created	2024-12-06
Platforms	java, mcp
Est. Tokens	~259k

About spring-ai-mcp

NOTE: This project has been graduated and moved to the MCP Java SDK and Spring AI MCP. See you there! This repository is now archived. Java & Spring MCP Set of projects that provide Java SDK and Spring Framework integration for the Model Context Protocol.

Compatible Skills

These tools work well together with spring-ai-mcp for enhanced workflows:

spring-ai-agent-utils — semantic(0.23)+complementary+shared_fw(spring)+same_lang+similar_pop+shared_platform (61%)
api2mcp4j — semantic(0.40)+shared_fw(spring)+rare_topics+same_lang+similar_pop+shared_platform (61%)
yu-ai-agent — semantic(0.46)+shared_fw(spring)+rare_topics+same_lang+similar_pop+shared_platform (59%)

spring-ai-mcp alternative? Top 6 similar tools

Looking for a spring-ai-mcp alternative? If you're comparing spring-ai-mcp with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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