Search Results for "call"

CodeGraph is a local-first code intelligence tool that gives AI coding agents a pre-indexed understanding of a repository. Instead of forcing agents to repeatedly scan files with grep, glob, and read commands, it builds a searchable knowledge graph of symbols, relationships, call graphs, and code structure. The project uses deterministic parsing rather than LLM summaries, which makes its indexed data more predictable and grounded in the actual source tree. It is designed for tools such as Claude Code, Codex, Cursor, and OpenCode, with MCP support for agent access. CodeGraph stores project data locally, which helps reduce token usage and repeated file exploration. ...

OpenConnector is an open-source integration gateway that gives AI agents controlled access to external applications and services. It exposes a shared catalog of more than 1,000 providers and over 10,000 predefined actions. Applications can call those actions through a TypeScript SDK, command-line relay, MCP, HTTP endpoints, or generated OpenAPI specifications. The runtime manages OAuth, API keys, custom credentials, scopes, tokens, policies, temporary files, and redacted logs. A web console helps administrators browse connectors, configure accounts, create runtime tokens, and inspect activity. ...

dsh-TUI is a full-screen terminal interface for DeepSeek Harness inspired by the interaction style of Claude Code. It streams Markdown, tool calls, reasoning status, token usage, context consumption, and throughput directly in the terminal. Users can resume, fork, compact, search, rewind, and switch models while preserving session history through DSH services. File references, image attachments, slash commands, questionnaires, and keyboard-driven input are built into the interface. Long...

...The system can inspect native binaries, JavaScript and Electron apps, managed assemblies, packages, and selected web applications. Agents can explore functions, strings, symbols, references, call graphs, assembly, and decompiled pseudocode. Analysis is designed to run locally and retain evidence behind each conclusion. REA can then help an agent translate what it learned into a compatible implementation for another project. It emphasizes explainable investigation rather than claiming to recover original source code.

Build intelligent agents quickly — inspired by the power of "Agentic workflows" and the Stanford DSPy paper. Seamlessly integrates with multiple LLMs and VectorDBs to build RAG pipelines or collaborative agents that can solve complex problems. Advanced features streaming validation, multi-modal DSPy, etc. We've renamed from "llmclient" to "ax" to highlight our focus on powering agentic workflows. We agree with many experts like "Andrew Ng" that agentic workflows are the key to unlocking the...