Searching software source code and locating software's API (application program interface) are important research issues in software engineering. As software projects are becoming more and more complex, existing search tools mainly face the following two challenges. First, more accurate search results are required in natural language question based search process. Second, the relationships between API are required to illustrate so that these API' underlying logic and usage scenarios are able to be understood more quickly. In this study, an ovel approach is proposed to searching a software project's API based on graph embedding. It aims to improve the accuracy of natural language based code graph search. A software project's code graph is built automatically from its source code and they are represented through graph embedding. For a natural language question, a code-connected subgraph, composed by relevant API and their associated relationships, are returned as the best answer. In experiments, Apache Lucene and POI projects are selected as examples to perform some API search tasks. Experimental results show that the proposed approach improves F1-score by 10% than existing shortest path based approach, while reduces average response time significantly.