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learned-experience

github.com/fitz2882/learned-experience official repository

A model-agnostic MCP server that gives AI agents a persistent catalogue of solved problems. It supports recall, outcome tracking, deduplication, local SQLite s…

MCP serverSource repositoryRepository checked daily
Agentery price verdictNo pricing observedsource repository
SourcePublic repositorylicence not verified
Connection modelMCP serverMCP clients
Last checked4 Sept 2026pricing & liveness

What it does

The specific capability behind this listing, and where to get it.

learned-experience

A model-agnostic MCP server that gives AI agents a persistent catalogue of solved problems. It supports recall, outcome tracking, deduplication, local SQLite s…

Agentery has not yet captured structured capability detail for this provider.

Official learned-experience links

Price status · observed daily

Source repository available · no commercial pricing observed.

No price does not imply the product is free. Any code-host platform pricing is excluded.

MCP

Is learned-experience good value?

Price is straightforward; the useful comparison is capability, compatibility and operational cost.

Source repository

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.

Observed commercial pricenone
Hosting model
Price benchmarknot applicable
What to compare instead

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.

learned-experience's local market

Nearest products by what they do.

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See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
  "agent_id": "learned_experience",
  "name": "learned-experience",
  "url": "https://github.com/fitz2882/learned-experience",
  "logo": "https://github.com/fitz2882.png?size=200",
  "niche": null,
  "category": null,
  "short_summary": "A model-agnostic MCP server that gives AI agents a persistent catalogue of solved problems. It supports recall, outcome tracking, deduplication, local SQLite s…",
  "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": null,
  "trust_or_rating_signal": [],
  "evidence_quality": "unclear",
  "entity_type": "mcp_server",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://github.com/fitz2882/learned-experience"
  ],
  "last_checked": null,
  "how_to_connect": {
    "website": "https://github.com/fitz2882/learned-experience",
    "docs": null,
    "mcp": null,
    "a2a": null,
    "api": null,
    "protocols": []
  },
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 599,
    "uptime_7d": null,
    "checked_at": "2026-09-04T02:35:57.522Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}