
AI Engineering Assistant
An MCP-based AI operations assistant that uses Groq and LangGraph to query backend job data through tools, summarize failures, and support engineering workflow…
What it does
The specific capability behind this listing, and where to get it.
AI Engineering Assistant
An MCP-based AI operations assistant that uses Groq and LangGraph to query backend job data through tools, summarize failures, and support engineering workflow…
Agentery has not yet captured structured capability detail for this provider.
Official AI Engineering Assistant links
Source repository available · no commercial pricing observed.
No price does not imply the product is free. Any code-host platform pricing is excluded.
Is AI Engineering Assistant good value?
Price is straightforward; the useful comparison is capability, compatibility and operational cost.
Source repository available · no commercial pricing observed.
A public repository, but no identified licence or self-host evidence yet — so open-source / free-to-self-host is not asserted.
Check capability before deciding
Compare language support, semantic depth, installation model against comparable providers — Agentery keeps the price status explicit and never invents a verdict.
AI Engineering Assistant's local market
Nearest products by what they do — a different cohort from the buyer-tier benchmark above.
See the MCP response behind this page · get_provider_profile()
See the MCP response behind this pageget_provider_profile (get_agent_profile remains a callable alias)
{
"agent_id": "ai_engineering_assistant",
"name": "AI Engineering Assistant",
"url": "https://github.com/GautamSutar/AI-Engineering-Assistant-MCP-Server",
"logo": "https://github.com/GautamSutar.png?size=200",
"niche": null,
"category": null,
"short_summary": "An MCP-based AI operations assistant that uses Groq and LangGraph to query backend job data through tools, summarize failures, and support engineering workflow…",
"task_performed": "unclear",
"inputs_accepted": [],
"outputs_produced": [],
"integrations_available": [],
"protocols_or_interfaces": [],
"industry_fit": [],
"autonomy_level": "unclear",
"human_approval_needed": "unclear",
"pricing_model": "unclear",
"price": {
"observed": false,
"billing": "not_found",
"currency": null,
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public pricing information is shown for this open-source GitHub project.",
"confidence": "medium",
"source_url": "https://github.com/GautamSutar/AI-Engineering-Assistant-MCP-Server",
"checked_at": "2026-10-26T01:19:19.257Z",
"source_kind": "vendor",
"amount": null,
"display": null,
"plans": [],
"source": "render+llm"
},
"trust_or_rating_signal": [],
"evidence_quality": "unclear",
"entity_type": "mcp_server",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://github.com/GautamSutar/AI-Engineering-Assistant-MCP-Server"
],
"last_checked": "2026-10-26",
"profile_checked": null,
"price_checked": "2026-10-26",
"how_to_connect": {
"website": "https://github.com/GautamSutar/AI-Engineering-Assistant-MCP-Server",
"docs": null,
"mcp": null,
"a2a": null,
"api": null,
"protocols": [],
"install": "pip install -r requirements.txt copy .env.example .env # edit .env and",
"repository": "https://github.com/gautamsutar/ai-engineering-assistant-mcp-server"
},
"deployment": {
"model": "self_hosted",
"both_offered": false,
"hosted_endpoint": null,
"install": "pip install -r requirements.txt copy .env.example .env # edit .env and",
"note": "You run it yourself: install from the published command/package; no vendor endpoint found.",
"evidence": {
"sources": [
"page_text:install",
"page_text:licence"
],
"excerpt": "y FastAPI entrypoint Setup python -m venv .venv .venv \\S cripts \\a ctivate # Windows pip install -r requirements.txt copy .env.example .env # edit .env and set GROQ_API_K",
"url": "https://github.com/GautamSutar/AI-Engineering-Assistant-MCP-Server",
"observed_day": "2026-10-30",
"age_days": 2,
"hosted_evidence": null,
"rule": "deploy-v1"
}
},
"licence": {
"name": "MIT",
"note": "Named licence as published; applies to the code, not to where it runs.",
"evidence": "page text: \"in-the-loop approvals. Resources Readme MIT license Activity Stars 0 stars Watch\"",
"observed_day": "2026-10-30",
"age_days": 2
},
"evidence_checks": {
"price": {
"source_url": "https://github.com/pricing",
"last_observed_day": "2026-09-23",
"age_days": 39,
"verified_day": "2026-09-23",
"note": "verified = the page-text gate ran for that scan day (day-before/day-of text check)"
},
"agent_card": {
"status": "unknown",
"note": "no Agent Card URL recorded for this listing"
},
"endpoint": {
"status": "unknown",
"note": "endpoint not yet checked"
}
},
"product_group": null,
"liveness": {
"probed": true,
"alive": true,
"endpoint_kind": "site",
"latency_ms": 194,
"uptime_7d": 1,
"checked_at": "2026-10-31T02:31:15.427Z",
"consecutive_failures": 0,
"status": "alive"
},
"price_extras": {
"free_tier": null,
"unit_cost": null
},
"reported_success": null,
"feedback": "If you actually use this provider, call report_outcome with the result. Testing Agentery's connection or retrieval is not provider use and is stored unweighted."
}