AgentKernel AI model data
REMOTE · WWW.AGENTKERNEL.SI
Live prices, rankings, licences and privacy of AI models: best model per task, costs, alternatives.
Available components
Last scanned (3 hours ago)
Scores higher than 60% of remote servers
Reachable. Last reached 17 Oct 2026.
Category AI and Machine Learning
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →
Endpoint Security80
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one. See how to fix → View diagnostics → Partial
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- The HSTS (Strict-Transport-Security) header is present. View diagnostics → Pass
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Transport & Reachability100
- Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass
Schema Quality & AI Usability61
- AI-judged instruction clarity (fair).Partial
- Tool/resource definitions use about 635 tokens (~105/item across 6 items; 6 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management10
- Stability observed for 3 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage76
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 27% of tool parameters carry a description.Partial
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 6 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 7 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 16 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.
- 15 Oct 26 0
- Stability: unverified → 0.03 ▲ functional
- 14 Oct 26 69
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 17 Oct 2026 · Probed https://www.agentkernel.si/mcp
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=*.agentkernel.si | CN=YR1,O=Let's Encrypt,C=US | 4 Oct 2026 | 2 Jan 2027 | RSA 2048 | SHA256-RSA | 64b57a4e4ebc0ac4272c452ad0d42d29cb0 |
| SANs: *.agentkernel.si, agentkernel.si | ||||||
| CN=YR1,O=Let's Encrypt,C=US (CA) | CN=Root YR,O=ISRG,C=US | 3 Sept 2025 | 2 Sept 2028 | RSA 2048 | SHA256-RSA | a20253f15f2691c05dc1ce13b9bcca4e |
| CN=Root YR,O=ISRG,C=US (CA) | CN=ISRG Root X1,O=Internet Security Research Group,C=US | 13 May 2026 | 2 Sept 2032 | RSA 4096 | SHA256-RSA | f24b6d17f9d9ad7cb1c9fea78782699f |
Background: What to check on a remote MCP endpoint →
DNSSEC insecure
Validation of www.agentkernel.si. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| si. | present | 42378 | 13 | Verified |
| agentkernel.si. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication No authorisation required
The endpoint answered without asking for a token. Anyone who knows the URL can reach it.
| Result | No authorisation required |
|---|---|
| HTTP status | 200 |
| Header | Value |
|---|---|
| strict-transport-security | max-age=63072000 |
| x-content-type-options | nosniff |
Background: How OAuth 2.1 works in the 2026 MCP spec →
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://www.agentkernel.si/mcp | Verified | 200 | |
| http (plaintext) | http://www.agentkernel.si/mcp | HTTPS enforced | 308 | https://www.agentkernel.si/mcp |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
best_for_task Best AI models for a task ~101
Ranks AI models for one task by performance only (price shown, never used for the rank). Tasks cover text, coding, agents, websites/UI/games/data viz, image generation and editing, video from text or image, video editing, text to speech, transcription, music and embeddings.
| Name | Type | Req | Description |
|---|---|---|---|
| license | string | – | open = open weights only, closed = proprietary only |
| limit | integer | – | – |
| task | string | yes | Task slug |
No output schema declared.
No examples provided.
cheaper_alternative Find a cheaper alternative ~55
For a model you use today, finds a cheaper model at most five performance-index points lower for the same usage.
| Name | Type | Req | Description |
|---|---|---|---|
| input_tokens | integer | – | – |
| model | string | yes | – |
| output_tokens | integer | – | – |
No output schema declared.
No examples provided.
estimate_cost Estimate API cost ~56
Monthly API cost at base rates for up to five models and a token volume, with the volume translated into words and pages.
| Name | Type | Req | Description |
|---|---|---|---|
| input_tokens | integer | – | – |
| models | array | yes | – |
| output_tokens | integer | – | – |
No output schema declared.
No examples provided.
find_models Search the model catalog ~82
Searches and filters the catalog of language models by name, provider, licence and privacy, sorted by performance, coding, agentic index, price or context.
| Name | Type | Req | Description |
|---|---|---|---|
| license | string | – | – |
| limit | integer | – | – |
| privacy | string | – | – |
| query | string | – | Part of a name, id or provider |
| sort | string | – | – |
No output schema declared.
No examples provided.
get_model Model facts ~93
Price, context window, performance/coding/agentic index with rank, licence, privacy, cost for a usage volume and cheaper or open alternatives for one language model.
| Name | Type | Req | Description |
|---|---|---|---|
| input_tokens | integer | – | – |
| model | string | yes | Model id like "anthropic/claude-opus-5.5" or a name like "Claude Opus 5.5" |
| output_tokens | integer | – | – |
No output schema declared.
No examples provided.
recommend_models Recommend models for a use case and budget ~141
Returns the best-fitting language models for a use case and monthly API budget using the published AgentKernel Fit Score (performance, cost, context, features), with optional privacy and licence requirements.
| Name | Type | Req | Description |
|---|---|---|---|
| include_free | boolean | – | – |
| input_tokens | integer | – | Input tokens per month |
| monthly_budget_usd | number | – | – |
| needs_vision | boolean | – | – |
| open_weights_only | boolean | – | – |
| output_tokens | integer | – | Output tokens per month |
| priority | string | – | – |
| privacy | string | – | zdr = zero data retention, eu = zero retention in an EU region |
| use_case | string | yes | – |
No output schema declared.
No examples provided.
How do I install the AgentKernel AI model data MCP server?
AgentKernel AI model data is a hosted endpoint at https://www.agentkernel.si/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
remote · www.agentkernel.si
claude mcp add --transport http si-agentkernel-models 'https://www.agentkernel.si/mcp'
What is the AgentKernel AI model data MCP server?
AgentKernel AI model data is an MCP server listed in the public MCP registry as si.agentkernel/models. Live prices, rankings, licences and privacy of AI models: best model per task, costs, alternatives. This page covers its hosted endpoint (https://www.agentkernel.si/mcp).
Is the AgentKernel AI model data MCP server safe to use?
AgentKernel AI model data scores 70 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the AgentKernel AI model data MCP server expose?
AgentKernel AI model data exposes 6 tools: best_for_task, recommend_models, get_model, find_models, estimate_cost, cheaper_alternative. Their descriptions and schemas cost roughly 528 tokens of context every time the server is loaded.
Does the AgentKernel AI model data MCP server require authentication?
No. We connected to AgentKernel AI model data without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.
Is the AgentKernel AI model data MCP server still maintained?
AgentKernel AI model data is still listed as active in the MCP registry. We last reached this channel on 17 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.