Deepcontext
Index your repo for semantic codebase search so agents retrieve the right files and symbols instead of guessing paths.
Overview
ai.wild-card/deepcontext is a MCP server for the Build phase that indexes codebases and exposes advanced semantic search to coding agents over stdio.
What is this MCP server?
- Advanced codebase indexing plus semantic search over your project
- stdio npm package @wildcard-ai/deepcontext at version 0.1.15
- Embeddings via JINA_API_KEY and vector storage via TURBOPUFFER_API_KEY
- Authenticated with WILDCARD_API_KEY per catalog environmentVariables
- Open source: github.com/Wildcard-Official/deepcontext
- Package @wildcard-ai/deepcontext version 0.1.15
- Transport: stdio (npm registry)
- 3 required secret env vars: JINA_API_KEY, TURBOPUFFER_API_KEY, WILDCARD_API_KEY
What problem does it solve?
Your agent loses time grepping huge repos and still misses the right module when context windows cannot hold the whole tree.
Who is it for?
Solo developers using agents daily on medium-to-large repos who already use or can set up Jina and Turbopuffer keys.
Skip if: Builders who only need occasional full-repo ripgrep with no embedding cost or external vector database setup.
What do I get? / Deliverables
Indexed semantic search over your project gives the agent precise file and concept hits during implementation and refactors.
- Searchable semantic index of project source
- Agent-queryable codebase context beyond raw file paste
- Repeatable stdio MCP integration for daily coding sessions
Recommended MCP Servers
Journey fit
During Build, agent quality depends on retrieval over large repos—especially for solo devs juggling multiple services alone. Agent-tooling is the canonical shelf for MCP servers that extend the coding agent’s context layer, not app feature code.
How it compares
Semantic codebase index MCP with external vector store, not a built-in IDE symbol search or generic web RAG plugin.
Common Questions / FAQ
Who is ai.wild-card/deepcontext for?
Developers shipping with AI agents who need dependable semantic retrieval across a real codebase and are willing to configure Jina, Turbopuffer, and Wildcard API credentials.
When should I use ai.wild-card/deepcontext?
Use it in Build when grep and manual file lists break down—onboarding to a fork, refactoring cross-cutting features, or hunting patterns across many packages.
How do I add ai.wild-card/deepcontext to my agent?
Install @wildcard-ai/deepcontext from npm, set JINA_API_KEY, TURBOPUFFER_API_KEY, and WILDCARD_API_KEY, then register the stdio MCP server in Claude Code or Cursor per your client’s npx/node command pattern.