Verified65% confidenceFactExact time
Before MCP emerged, the integration of large language models with external tools was highly fragmented, with OpenAI's Function Calling, LangChain's Tool framework, and various vendor plugin mechanisms being mutually incompatible.
3
Sources
65%
Confidence
Long-term
Relevance
7/17/2026
First Seen
Sources
Related Claims
VerifiedBefore MCP, the interaction between large models and external tools mainly relied on vendor-defined Function Calling mechanisms, with OpenAI and Google Gemini each having different function calling formats that were mutually incompatible.85% similarUnverified在MCP出现前存在LangChain Tools、OpenAI Function Calling等多套互不兼容的集成规范，造成生态碎片化85% similarVerified在MCP出现之前，AI调用外部工具主要依赖OpenAI的Function Calling机制或各框架自定义的插件系统83% similarVerifiedMCP aims to address the fragmentation problem in connecting large language models with external data sources and tools.79% similarUnverifiedOpenAI's Function Calling, Anthropic's Tool Use, and the MCP protocol all rely on JSON Schema as the description language for tool interface contracts.79% similar
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