GraphCanon updated 1mo · GitHub synced 1mo
Decision brief
Incognide is a TypeScript library for developing AI agents with integrated capabilities for llm-inference.
Good fit when
- When you need a TypeScript-based solution to develop AI agents that integrate llm-inference features
- Ideal for projects involving artificial intelligence research and development
Avoid when
- If your project requires languages other than TypeScript as the primary language
- Not suitable if you are looking for ready-to-deploy production tools, given its focus on research and development phase
Observed Jul 16, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (3d since push)
- As of 1mo
- Provenance
- Not a fork · Organization account
- As of 1mo
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install incognideSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A TypeScript-based repository focusing on creating AI agents with integration for llm-inference, ideal for research and development involving artificial intelligence.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Jul 26, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Jul 26, 2026
- CLI
- CLI entrypoint
Source: package.json:bin|scripts · Jul 26, 2026
- MCP server
- No MCP server detected
Source: repo_scan · Jul 26, 2026
- Languages
- typescript, javascript
Source: github.language+package.json · Jul 26, 2026
Categories
Tags
README
1. Install
Download the installer for your platform from enpisi.com/incognide, run it, and launch Incognide. Linux, macOS, and Windows are supported.
License
Incognide is licensed under the MIT License. See the LICENSE file for details.
For agents
This page has a .md twin and JSON over the API.