
Gigaxity Deep Research
Open-source MCP server for deep research synthesis. Integrates reasoning models (Qwen3, DeepSeek-R1) with multi-source web search, RRF fusion, and citation bin…
What it does
The specific capability behind this listing, and where to get it.
Gigaxity Deep Research
Open-source MCP server for deep research synthesis. Integrates reasoning models (Qwen3, DeepSeek-R1) with multi-source web search, RRF fusion, and citation bin…
Official Gigaxity Deep Research links
Pricing & plans
Observed public pricing for Gigaxity Deep Research, benchmarked against comparable providers. Plans, tiers, history and scenario below.
$4 /mo
The current price sits below the comparable median.
$4 sits below the observed Team flat range ($386.63–$523.09) — around the 25th percentile of observed prices. It reads as a value play; make sure the margin still works.
Why Agentery reaches that view
price_benchmark99.1% below the Team flat median.
get_provider_profile · plan historyTeam observed 2026-07-15.
pricing recommendation~25th percentile of comparable Team flat plans (approximate: interpolated between the cohort’s observed quartiles, 3 providers).
confidencethin (thin cohort); source page rechecked daily.
Test a different price for this plan.
Move the proposed monthly price. Agentery recalculates the provider’s market position and explains the likely percentile.
Is Gigaxity Deep Research good value?
How its price compares with genuinely comparable providers.
Below the comparable median for its buyer tier.
Basis: Team flat plans at the same billing unit (3 providers), USD monthly, pricing observed 2026-07-15. The Team plan ($4/mo) sits 99.1% below that median of $454.86. Thin evidence: fewer than five comparable providers, so treat the position as indicative. Other cohorts on this page (niche-wide tier peers, nearest products by capability) are labelled where they appear.
Compared with Deep Research Agent
Positioned against the observed p25 / median / p75 of comparable providers at the same buyer tier and billing unit (the basis is stated with each verdict above). See the plans above for the percentile and its cohort size, and the full niche market for peers.
View the full niche →Gigaxity Deep Research'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": "gigaxity_deep_research",
"name": "Gigaxity Deep Research",
"url": "https://github.com/yoloshii/gigaxity-deep-research",
"logo": "https://github.com/yoloshii.png?size=200",
"niche": "deep-research-agent",
"category": "research-knowledge-work",
"short_summary": "Open-source MCP server for deep research synthesis. Integrates reasoning models (Qwen3, DeepSeek-R1) with multi-source web search, RRF fusion, and citation bin…",
"task_performed": "unclear",
"inputs_accepted": [],
"outputs_produced": [],
"integrations_available": [],
"protocols_or_interfaces": [
"MCP"
],
"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 or paid plans are shown; the project is presented as an open-source MIT-licensed repository.",
"confidence": "medium",
"source_url": "https://github.com/yoloshii/gigaxity-deep-research",
"checked_at": "2026-10-23T01:57:35.274Z",
"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/yoloshii/gigaxity-deep-research"
],
"last_checked": "2026-10-23",
"profile_checked": null,
"price_checked": "2026-10-23",
"how_to_connect": {
"website": "https://github.com/yoloshii/gigaxity-deep-research",
"docs": null,
"mcp": null,
"a2a": null,
"api": null,
"protocols": [
"MCP"
],
"install": "git clone https://github.com/yoloshii/gigaxity-deep-research.git cd gigaxity-deep-researc",
"repository": "https://github.com/yoloshii/gigaxity-deep-research",
"note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
},
"deployment": {
"model": "both",
"both_offered": true,
"hosted_endpoint": null,
"install": "git clone https://github.com/yoloshii/gigaxity-deep-research.git cd gigaxity-deep-researc",
"note": "Offered both ways: a vendor-hosted endpoint AND a self-run install are documented.",
"evidence": {
"sources": [
"page_text:hosted",
"page_text:install",
"page_text:licence",
"page_text:both_offered"
],
"excerpt": "LLM endpoint Start a local model (vLLM / SGLang / llama.cpp) or point env vars at a hosted endpoint such as OpenRouter curl $RESEARCH_LLM_API_BASE/models returns a model",
"url": "https://github.com/yoloshii/gigaxity-deep-research",
"observed_day": "2026-10-25",
"age_days": 1,
"hosted_evidence": "wording: \"hosted endpoint\"",
"rule": "deploy-v1"
}
},
"licence": {
"name": "MIT",
"note": "Named licence as published; applies to the code, not to where it runs.",
"evidence": "page text: \"nthesis searxng tavily Resources Readme MIT license Code of conduct Code of cond\"",
"observed_day": "2026-10-25",
"age_days": 1
},
"evidence_checks": {
"price": {
"source_url": "https://github.com/pricing",
"last_observed_day": "2026-09-20",
"age_days": 36,
"verified_day": null,
"note": "not verified by the page-text gate"
},
"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": 684,
"uptime_7d": 1,
"checked_at": "2026-10-26T02:36:14.536Z",
"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."
}