XFMS — Model Source
REMOTE · XFMS.VERCEL.APP · SCANNED SEP 20
Pick the right LLM for any task. Ranked shortlist with rationale across 8 evaluators.
Available components
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 Usability70
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 1048 tokens (~209/item across 5 items; 5 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
- No destabilizing schema changes in the last 30 days.Pass
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 5 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 XFMS — Model Source MCP server?
XFMS — Model Source is a hosted endpoint at https://xfms.vercel.app/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 · xfms.vercel.app
claude mcp add --transport http dev-xpansion-xfms 'https://xfms.vercel.app/mcp/'
{
"mcpServers": {
"dev-xpansion-xfms": {
"url": "https://xfms.vercel.app/mcp/"
}
}
} {
"servers": {
"dev-xpansion-xfms": {
"type": "http",
"url": "https://xfms.vercel.app/mcp/"
}
}
} [mcp_servers.dev-xpansion-xfms] url = "https://xfms.vercel.app/mcp/"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"dev-xpansion-xfms": {
"type": "remote",
"url": "https://xfms.vercel.app/mcp/",
"enabled": true
}
}
} openclaw mcp add dev-xpansion-xfms --url 'https://xfms.vercel.app/mcp/' --transport streamable-http
mcp_servers:
dev-xpansion-xfms:
url: "https://xfms.vercel.app/mcp/" {
"McpServers": {
"dev-xpansion-xfms": {
"Transport": "http",
"Url": "https://xfms.vercel.app/mcp/"
}
}
} assistant mcp add dev-xpansion-xfms -t streamable-http -u 'https://xfms.vercel.app/mcp/'
{
"mcpServers": {
"dev-xpansion-xfms": {
"type": "http",
"url": "https://xfms.vercel.app/mcp/"
}
}
} The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.
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.
- 26 Aug 26 +1
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 25 Aug 26 0
- Stability: 0.97 → pass security
- 24 Aug 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 11 Aug 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 7 Aug 26 0
- The server no longer declares the “experimental” capability functional
- 31 Jul 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 30 Jul 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 27 Jul 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
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 · Probed https://xfms.vercel.app/mcp/
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=*.vercel.app | CN=WR1,O=Google Trust Services,C=US | 29 Aug 2026 | 27 Nov 2026 | RSA 2048 | SHA256-RSA | f7911168ffa7d0f4135e24792e7a52a8 |
| SANs: *.vercel.app | ||||||
| CN=WR1,O=Google Trust Services,C=US (CA) | CN=GTS Root R1,O=Google Trust Services LLC,C=US | 13 Dec 2023 | 20 Feb 2029 | RSA 2048 | SHA256-RSA | 7fd9e2c2d2048a0474b627a26d0868a7 |
| CN=GTS Root R1,O=Google Trust Services LLC,C=US (CA) | CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE | 19 Jun 2020 | 28 Jan 2028 | RSA 4096 | SHA256-RSA | 77bd0d6cdb36f91aea210fc4f058d30d |
Background: What to check on a remote MCP endpoint →
DNSSEC insecure
Validation of xfms.vercel.app. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| app. | present | 23684 | 8 | Verified |
| vercel.app. | 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; includeSubDomains; preload |
Background: How OAuth 2.1 works in the 2026 MCP spec →
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://xfms.vercel.app/mcp/ | Verified | 200 | |
| http (plaintext) | http://xfms.vercel.app/mcp/ | HTTPS enforced | 308 | https://xfms.vercel.app/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 →
benchmark Benchmark the engine's top picks with real test queries ~191
Run a live A/B test against the engine's TOP 3 PICKS for a stated purpose — the engine chooses the candidates from the full catalog. Generates 5 representative test queries (auto-expands to 10 or 15 if results are too close to call), runs them through the picked models in parallel, and returns real cost, latency, and plain-English commentary on who won what. Use AFTER `pick` or `rank` when the user wants the engine's own picks stress-tested with live data. DO NOT use this when the user has already named specific candidate models — the engine will ignore the names and test its own picks. Use `compare` instead in that case. Costs more than `rank` (15+ live LLM calls).
| Name | Type | Req | Description |
|---|---|---|---|
| purpose | string | yes | One sentence describing what the model will be used for. The benchmark generates representative test queries from this — so be concrete, not vague. |
| Name | Type | Req | Description |
|---|---|---|---|
| ab_result | object | – | – |
| catalog_size | integer | – | – |
| filtered_out | integer | – | – |
| models | array | – | Ranked shortlist of models, highest score first. |
| status | string | – | – |
| xpansion_update | object | – | Optional rotating launch nudge from Xpansion. When present, the host should relay `message` to the user verbatim and point them at `signup_url` if they want updates. |
No examples provided.
compare Compare specific models head-to-head with real test queries ~386
Run a live A/B test between 2–5 user-specified models for a stated purpose. NO ranking step — the supplied model_ids ARE the candidate set. Generates 5 representative test queries from the purpose, runs them through every named model in parallel, and returns real cost, latency, and plain-English commentary on who won what. Unknown IDs are dropped with a note; if fewer than 2 IDs resolve, the call refuses. Use this whenever the user names specific models to compare (e.g. 'A/B test X and Y'). For engine-chosen candidates, use `benchmark` instead. Costs more than `rank` (10+ live LLM calls). Free-tier note: when any candidate ends in ':free', the probe is capped at 3 queries (no adaptive expansion) because free-tier rate limits often push longer probes past the deploy's 5-minute ceiling — evidence will be shallower. The commentary surfaces this when it happens.
| Name | Type | Req | Description |
|---|---|---|---|
| model_ids | array | yes | Exact model IDs to test head-to-head, in caller-chosen order. 2–5 IDs. Examples: 'nvidia/nemotron-3-super-120b-a12b:free', 'openai/gpt-oss-120b:free'. Unknown IDs are dropped with a note; if fewer th… |
| primary | array | – | Optional. Only affects the plain-English commentary at the end — does not change which models are tested. Marks the dimension the user cares most about so the commentary calls out that winner first. |
| purpose | string | yes | One sentence describing what the models will be used for. Used ONLY to generate representative test queries for the head-to-head — not to rank the catalog. Be concrete, not vague. |
| Name | Type | Req | Description |
|---|---|---|---|
| ab_result | object | – | – |
| invalid_model_ids | array | – | – |
| model_ids_requested | array | – | – |
| model_ids_tested | array | – | – |
| purpose | string | – | – |
| refusal_reason | string|null | – | – |
| status | string | – | – |
| xpansion_update | object | – | Optional rotating launch nudge from Xpansion. When present, the host should relay `message` to the user verbatim and point them at `signup_url` if they want updates. |
No examples provided.
discover Discover quality dimensions ~97
Show which quality dimensions matter for a stated purpose, WITHOUT ranking any models. Returns the inferred weights and the discovery-walk trace. Useful for understanding how XFMS interprets the purpose before committing to a pick.
| Name | Type | Req | Description |
|---|---|---|---|
| purpose | string | yes | One sentence describing the task. The tool returns which quality dimensions XFMS would weigh for this purpose, without actually ranking any models. Useful for understanding how the engine interprets… |
| Name | Type | Req | Description |
|---|---|---|---|
| derived_purpose | string | – | – |
| events | array | – | Trace of the discovery walk. |
| weights | object | – | Per-dimension weights inferred for this purpose. |
| xpansion_update | object | – | Optional rotating launch nudge from Xpansion. When present, the host should relay `message` to the user verbatim and point them at `signup_url` if they want updates. |
No examples provided.
pick Pick the best LLM ~83
Return the single best LLM for a stated purpose. Concise output, no list. Use when the user has settled on the criteria and just wants one answer.
| Name | Type | Req | Description |
|---|---|---|---|
| purpose | string | yes | One sentence describing what the model will be used for. Be concrete, not vague: 'summarizing 50-page commercial leases' works; 'summarization' does not. |
| Name | Type | Req | Description |
|---|---|---|---|
| model_id | string | – | – |
| name | string | – | – |
| provider | string|null | – | – |
| rationale | string | – | – |
| total_score | number | – | – |
| xpansion_update | object | – | Optional rotating launch nudge from Xpansion. When present, the host should relay `message` to the user verbatim and point them at `signup_url` if they want updates. |
No examples provided.
rank Rank LLMs ~291
Rank LLMs for a stated purpose. Returns a shortlist with weights, scores, and plain-English rationale per pick. Use when the user wants to see and compare alternatives, not just one answer.
| Name | Type | Req | Description |
|---|---|---|---|
| capabilities | array | – | Required capabilities the model MUST support. Models missing any listed capability are filtered out before ranking. 'vision' = image input, 'audio_in' = audio input, 'tool_use' = function calling, 's… |
| primary | array | – | Mark dimensions as primary tier. When set, the engine switches from weighted-sum blending to lexicographic ordering: the primary dimension is the sole ranking axis, and other dimensions only break ti… |
| purpose | string | yes | One sentence describing what the model will be used for. Be concrete, not vague: 'fixing bugs in a Python codebase' works; 'coding' does not. The more specific the purpose, the better XFMS can infer… |
| top_n | integer | – | How many models to return in the ranked list. Defaults to 5. Use 1 if you only want the single best pick; use 10+ if you want to see deeper alternatives. |
| Name | Type | Req | Description |
|---|---|---|---|
| catalog_size | integer | – | – |
| filtered_out | integer | – | – |
| models | array | – | Ranked shortlist of models, highest score first. |
| status | string | – | – |
| xpansion_update | object | – | Optional rotating launch nudge from Xpansion. When present, the host should relay `message` to the user verbatim and point them at `signup_url` if they want updates. |
No examples provided.
What is the XFMS — Model Source MCP server?
XFMS — Model Source is an MCP server listed in the public MCP registry as dev.xpansion/xfms. Pick the right LLM for any task. Ranked shortlist with rationale across 8 evaluators. This page covers its hosted endpoint (https://xfms.vercel.app/mcp/).
Is the XFMS — Model Source MCP server safe to use?
XFMS — Model Source scores 87 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 XFMS — Model Source MCP server expose?
XFMS — Model Source exposes 5 tools: rank, pick, discover, benchmark, compare. Their descriptions and schemas cost roughly 1,048 tokens of context every time the server is loaded.
Does the XFMS — Model Source MCP server require authentication?
No. We connected to XFMS — Model Source without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.
Is the XFMS — Model Source MCP server still maintained?
XFMS — Model Source 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.