
Ultimate
Provides an MCP server exposing dozens of capabilities to AI agents: cognitive memory, browser automation, Excel manipulation, database interactions, document…
What it does
The specific capability behind this listing, and where to get it.
Provides an MCP server exposing dozens of capabilities to AI agents: cognitive memory, browser automation, Excel manipulation, database interactions, document processing, OCR, vector operations, entity relation graphs, audio transcription, and LLM provider orchestration/task delegation
Source repository available · no commercial pricing observed.
No price does not imply the product is free. Any code-host platform pricing is excluded.
Is Ultimate 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.
View the full niche →Comparable AI Agent Integration Platform
Alternatives in the same niche, with observed price and liveness where available.



See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
"agent_id": "ultimate_mcp_server",
"name": "Ultimate",
"url": "https://github.com/dicklesworthstone/ultimate_mcp_server",
"logo": "https://agentery.com/logos/CP-4J57KP-256.png",
"niche": "ai-agent-integration-platform",
"category": "developer-tools-infra",
"short_summary": "Provides an MCP server exposing dozens of capabilities to AI agents: cognitive memory, browser automation, Excel manipulation, database interactions, document…",
"task_performed": "Provides an MCP server exposing dozens of capabilities to AI agents: cognitive memory, browser automation, Excel manipulation, database interactions, document processing, OCR, vector operations, entity relation graphs, audio transcription, and LLM provider orchestration/task delegation",
"inputs_accepted": [
"MCP tool calls from AI agents",
"documents (PDF",
"Excel)",
"web pages",
"database queries",
"audio",
"API calls"
],
"outputs_produced": [
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"transcriptions",
"LLM completions",
"orchestrated workflow outputs"
],
"integrations_available": [
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"Claude",
"OpenAI",
"Anthropic",
"Gemini",
"Marqo",
"FastMCP",
"streaming-http",
"SSE",
"stdio",
"Docker"
],
"protocols_or_interfaces": [
"MCP"
],
"industry_fit": [
"developer tools"
],
"autonomy_level": "infrastructure",
"human_approval_needed": "unclear",
"pricing_model": "free",
"price": {
"observed": false,
"billing": "not_found",
"currency": null,
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": null,
"summary": null,
"confidence": "high",
"source_url": "https://github.com/pricing",
"checked_at": "2026-07-26T07:57:33.764Z",
"amount": null,
"display": null,
"plans": [],
"source": "render+llm"
},
"trust_or_rating_signal": [
"151 GitHub stars",
"24 forks",
"MIT license",
"CI/CD GitHub Actions workflows"
],
"evidence_quality": "high",
"entity_type": "infrastructure",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://github.com/dicklesworthstone/ultimate_mcp_server"
],
"last_checked": "2026-06-16",
"how_to_connect": {
"website": "https://github.com/dicklesworthstone/ultimate_mcp_server",
"docs": "https://github.com/documentation",
"mcp": {
"endpoint": "https://github.com/mcp.json",
"transport": "http",
"config_snippet": "{\n \"mcpServers\": {\n \"ultimate_mcp_server\": {\n \"url\": \"https://github.com/mcp.json\"\n }\n }\n}"
},
"a2a": null,
"api": {
"docs_url": "https://github.com/developer",
"endpoint": null
},
"protocols": []
},
"liveness": {
"probed": true,
"alive": true,
"endpoint_kind": "site",
"latency_ms": 634,
"uptime_7d": 1,
"checked_at": "2026-07-28T02:39:11.113Z",
"consecutive_failures": 0,
"status": "alive"
},
"price_extras": {
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"unit_cost": null
},
"reported_success": null,
"feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}