llm-oracle
NPM · @WEISEER/LLM-ORACLE-MCP · SCANNED SEP 20
Up-to-date LLM pricing + availability catalog with cited sources for AI agent routing.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 31 of 95 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 113 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability59
- AI-judged instruction clarity (fair).Partial
- Tool/resource definitions use about 427 tokens (~53/item across 8 items; 8 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management93
- Stability observed for 28 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage67
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 8 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 8 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
How do I install the llm-oracle MCP server?
llm-oracle runs locally as an npm package, launched with npx -y @weiseer/llm-oracle-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · @weiseer/llm-oracle-mcp
claude mcp add weiseer-llm-oracle -- npx -y @weiseer/llm-oracle-mcp
{
"mcpServers": {
"weiseer-llm-oracle": {
"command": "npx",
"args": [
"-y",
"@weiseer/llm-oracle-mcp"
]
}
}
} {
"servers": {
"weiseer-llm-oracle": {
"command": "npx",
"args": [
"-y",
"@weiseer/llm-oracle-mcp"
]
}
}
} codex mcp add weiseer-llm-oracle -- npx -y @weiseer/llm-oracle-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"weiseer-llm-oracle": {
"type": "local",
"command": [
"npx",
"-y",
"@weiseer/llm-oracle-mcp"
],
"enabled": true
}
}
} openclaw mcp add weiseer-llm-oracle --command npx --arg -y --arg @weiseer/llm-oracle-mcp
mcp_servers:
weiseer-llm-oracle:
command: "npx"
args: ["-y", "@weiseer/llm-oracle-mcp"] {
"McpServers": {
"weiseer-llm-oracle": {
"Transport": "stdio",
"Command": "npx",
"Arguments": [
"-y",
"@weiseer/llm-oracle-mcp"
]
}
}
} assistant mcp add weiseer-llm-oracle -t stdio -c npx -a -y @weiseer/llm-oracle-mcp
{
"mcpServers": {
"weiseer-llm-oracle": {
"command": "npx",
"args": [
"-y",
"@weiseer/llm-oracle-mcp"
]
}
}
} 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.
- 18 Sept 26 +1
- Security disclosure: unverified → fail ▼ functional
- 17 Sept 26 0
- Security disclosure: fail → unverified ▼ functional
- 16 Sept 26 −2
- Stability: pass → 0.80 functional
- 15 Sept 26 0
- Stability: 0.97 → pass security
- Security disclosure: unverified → fail ▼ functional
- 14 Sept 26 +1
- Security disclosure: fail → unverified ▼ functional
- 11 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.
- 10 Sept 26 −2
- Stability: pass → 0.83 functional
- 9 Sept 26 0
- Stability: 0.97 → pass security
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 20 Sept 2026 · Analysed npm/@weiseer/llm-oracle-mcp@0.2.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Dependencies 95 packages
| Packages resolved | 95 |
|---|---|
| Stale | 31 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
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 →
check_availability ~28
Current availability status for a model with cited source URL.
| Name | Type | Req | Description |
|---|---|---|---|
| model_id | string | yes | – |
No output schema declared.
No examples provided.
compare_models ~46
Side-by-side comparison of a set of models for a token spec.
| Name | Type | Req | Description |
|---|---|---|---|
| input_tokens | number | – | – |
| model_ids | array | yes | – |
| output_tokens | number | – | – |
No output schema declared.
No examples provided.
estimate_monthly_cost ~69
Projected monthly + yearly cost for a model given call volume + avg token spec. Useful for AI app capacity planning.
| Name | Type | Req | Description |
|---|---|---|---|
| avg_input_tokens | number | – | – |
| avg_output_tokens | number | – | – |
| calls_per_day | number | yes | – |
| model_id | string | yes | – |
No output schema declared.
No examples provided.
find_cheapest ~55
Rank models by estimated cost for token spec; cheapest first.
| Name | Type | Req | Description |
|---|---|---|---|
| input_tokens | number | yes | – |
| only_operational | boolean | – | – |
| output_tokens | number | yes | – |
| required_capabilities | array | – | – |
No output schema declared.
No examples provided.
get_model ~29
Full record for one model id with cited pricing/availability URLs.
| Name | Type | Req | Description |
|---|---|---|---|
| model_id | string | yes | – |
No output schema declared.
No examples provided.
list_models ~35
List LLM models, optionally filtered by provider or required capability.
| Name | Type | Req | Description |
|---|---|---|---|
| capability | string | – | – |
| provider | string | – | – |
No output schema declared.
No examples provided.
pick_optimal_model ~114
Multi-criteria routing recommendation — weighted cost/speed/quality, with rationale. THIS is what AI agents should call instead of find_cheapest when they care about more than just cost.
| Name | Type | Req | Description |
|---|---|---|---|
| allowed_providers | array | – | – |
| cost_weight | number | – | – |
| input_tokens | number | yes | – |
| min_context_window | number | – | – |
| output_tokens | number | yes | – |
| quality_weight | number | – | – |
| required_capabilities | array | – | – |
| speed_weight | number | – | – |
No output schema declared.
No examples provided.
recommend_fallback ~51
Given a primary model, recommend fallback candidates with same capabilities, cross-provider preferred for diversification.
| Name | Type | Req | Description |
|---|---|---|---|
| input_tokens | number | – | – |
| model_id | string | yes | – |
| output_tokens | number | – | – |
No output schema declared.
No examples provided.
What is the llm-oracle MCP server?
llm-oracle is an MCP server listed in the public MCP registry as io.github.weiseer/llm-oracle. Up-to-date LLM pricing + availability catalog with cited sources for AI agent routing. This page covers its npm package (@weiseer/llm-oracle-mcp).
Is the llm-oracle MCP server safe to use?
llm-oracle scores 77 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. It declares no install or post-install scripts. 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 llm-oracle MCP server expose?
llm-oracle exposes 8 tools: list_models, get_model, find_cheapest, compare_models, check_availability, and 3 more. Their descriptions and schemas cost roughly 427 tokens of context every time the server is loaded.
Is the llm-oracle MCP server still maintained?
llm-oracle is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the llm-oracle MCP server under?
llm-oracle declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.