Agents @Kopern.ai
https://kopern.ai/api/mcp/server ↗
Description
Full AI agent lifecycle platform — create, grade, optimize, deploy and orchestrate AI agents from your IDE or terminal. ## What you can do - **Build** — Create agents from 37 templates or custom system prompts, with skills, tools and extensions - **Grade** — Evaluate agent quality with 6 criteria (output match, schema validation, tool usage, safety, custom scripts, LLM judge) - **Optimize** — AutoResearch lab with 6 modes: AutoTune, AutoFix, Stress Lab, Tournament, Distillation, Evolution - **Deploy** — Widget, Slack, Telegram, WhatsApp, webhooks (n8n/Zapier/Make compatible) - **Orchestrate** — Multi-agent teams with parallel, sequential and conditional execution modes - **Monitor** — Usage tracking, session history, compliance reports (EU AI Act) ## 32 tools in 6 categories | Category | Tools | |----------|-------| | Agent CRUD | create, get, update, delete, list, import, export | | Templates | list templates, deploy template | | Grading | grade prompt, create suite, run grading,
What our measurements say
Agents @Kopern.ai is a remote MCP server published at kopern.ai. It has been probed 7 times since 9/10/2026. It answered in 7 of them (100.0%), a near-uninterrupted record. Median response time is 448 ms, placing it among the faster endpoints. It exposes a broad tool surface of 31 tools. On the protocol side it still runs 2025-11-25 and has not moved to the newer spec.
Agent readability score
Can an LLM agent pick the right tool here — names, descriptions and parameter clarity are assessed.
Agent readability score
Strengths
- Tool names clearly indicate their purpose (e.g., 'kopern_list_agents')
- Descriptions explain outcomes and use cases for most tools
- Many tools explicitly state 'No LLM cost' for transparency
Weaknesses
- Some descriptions lack specific usage scenarios (e.g., 'kopern_grade_prompt' doesn't clarify when to use each grading criterion)
- Parameter definitions are missing in inputSchema summaries
- Error handling and constraints are not documented for API key-dependent tools
kopern_grade_prompt— Test case parameters for grading criteria are not specifiedkopern_run_autoresearch— Optimization mode parameters are not detailedkopern_connect_telegram— No mention of error handling for invalid bot tokens
Verdict
Event narrative
Risk: medium
- 2026-09-10T21:16:35.016Z — era changed from null to auth-gated, complianceScore and smokeOk initialized to null · Initial state with no compliance data or smoke test results
- 2026-09-11T03:50:39.090Z — era changed from auth-gated to legacy, complianceScore rose from null to 100, smokeOk changed from null to false · Improved compliance but smoke test failure indicates potential operational issues
Advice
Schema compliance
tools/list structure, inputSchema validity, and a functional smoke test — the components of the 0-100 score.
- tools/list schema valid
- inputSchema is valid JSON Schema
- Smoke test failed · last run:
- Cold-start: cold 157ms → warm 217ms (penalty 0ms)
Availability history
Event log
Derived by comparing consecutive probes — changes in era, protocol version, build and reachability.
- Server build: — → 2.0.0
- Supported versions: — → 2024-11-05
- Era changed: Auth-gated → Legacy
- Added to watch — era: Auth-gated
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