Open Issues Need Help
View All on GitHubAI Summary: `semantic_code_search` in Context+ consistently fails with an "input length exceeds context length" error when used on codebases containing over 100 files, regardless of query length or model context size. This issue appears specific to `semantic_code_search` and Ollama, as direct embedding API calls and `semantic_identifier_search` function correctly with the same models and codebase.
Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy. By combining Tree-sitter AST parsing, Spectral Clustering, and Obsidian-style linking, Context+ turns a massive codebase into a searchable, hierarchical feature graph.
Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy. By combining Tree-sitter AST parsing, Spectral Clustering, and Obsidian-style linking, Context+ turns a massive codebase into a searchable, hierarchical feature graph.
Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy. By combining Tree-sitter AST parsing, Spectral Clustering, and Obsidian-style linking, Context+ turns a massive codebase into a searchable, hierarchical feature graph.