# Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking (remote · onvexia.com)

Crypto fundamental analysis, sentiment and whale tracking for traders and AI agents.

- Trust score: 73/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-20

## Components

- remote · `onvexia.com`: 73/100 (this document), [markdown](https://verifymcp.io/servers/com-onvexia-onvexia/onvexia.md), [page](https://verifymcp.io/servers/com-onvexia-onvexia/onvexia)

## Channel facts

- Endpoint: `https://onvexia.com/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.7`

## Trust breakdown

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. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-20.

- **Endpoint Security**: 80/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 74/100
  - AI-judged instruction clarity (good).
  - Tool/resource definitions use about 5868 tokens (~88/item across 66 items; 66 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 13/100
  - Stability observed for 4 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 67/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 0% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 66 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 67 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

## Install

### How do I install the Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking MCP server?

Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking is a hosted endpoint at https://onvexia.com/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.

### Claude

```bash
claude mcp add --transport http com-onvexia-onvexia 'https://onvexia.com/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "com-onvexia-onvexia": {
      "url": "https://onvexia.com/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "com-onvexia-onvexia": {
      "type": "http",
      "url": "https://onvexia.com/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.com-onvexia-onvexia]
url = "https://onvexia.com/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-onvexia-onvexia": {
      "type": "remote",
      "url": "https://onvexia.com/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-onvexia-onvexia --url 'https://onvexia.com/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-onvexia-onvexia:
    url: "https://onvexia.com/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "com-onvexia-onvexia": {
      "Transport": "http",
      "Url": "https://onvexia.com/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add com-onvexia-onvexia -t streamable-http -u 'https://onvexia.com/mcp'
```

### Other

```json
{
  "mcpServers": {
    "com-onvexia-onvexia": {
      "type": "http",
      "url": "https://onvexia.com/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-20 (score 73, +1)

No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-18 (score 72, +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.

### 2026-09-17 (score 71, 0)

- [functional improvement] Stability: unverified → 0.03

### 2026-09-16 (score 71)

First indexed and scored.

## MCP tools (66)

### `get_asset` (~90 tokens)

Assets · Profile

An asset's core profile by symbol: name, category and cross-system
        identifiers (CoinGecko id, contract addresses, chains).

        Start here when you have a ticker and need to be sure which asset it
        refers to. Tickers collide across chains — if the symbol is ambiguous,
        resolve_ticker is the tool that says so instead of guessing.

Input parameters:

- `symbol` (string, required)

### `get_asset_scores` (~105 tokens)

Scores · Asset breakdown

An asset's Galaxy Score and AltRank, with the components behind each.

        Galaxy Score is a composite of social and market health on a 0-100
        scale; AltRank is relative standing against the rest of the universe,
        where 1 is best. READ THE COMPONENT BREAKDOWN — a score moved by
        sentiment and one moved by volume mean different things, and the
        composite alone cannot tell you which happened.

Input parameters:

- `symbol` (string, required)

### `get_asset_fundamentals` (~207 tokens)

Fundamentals · Full brief

Get the full fundamental brief for an asset: market snapshot, supply
        and valuation, project, TVL, revenue, treasury, security, governance,
        unlock schedule, derivatives positioning, competitive rank, valuation
        ratios and a graded scorecard — in one call.

        READ THE SECTION STATES, NOT ONLY THE VALUES. Each section is
        `measured`, `not_held` or `failed`, and sections the asset class cannot
        have are returned separately in `not_applicable`. "This chain has no
        DAO treasury" and "we could not read it" are different facts and this
        response keeps them apart.

        Revenue is split: `S06` is the entity's own fees, `S06b` is the total
        earned by protocols deployed on a chain. The two can differ by two
        orders of magnitude and only the first accrues to the token.

Input parameters:

- `symbol` (string, required)

### `get_asset_technicals` (~199 tokens)

Fundamentals · Technical levels

Get support and resistance merged across 1w/1d/4h/1h, per-timeframe
        indicators, and derived spot/long/short setups for an asset.

        Each level carries the timeframes that confirmed it and the method on
        each — a level agreed by four charts is a different claim from one seen
        on the hourly. `measured_against` names the exchange and pair every
        distance was computed from, and `price_age_minutes` says how old that
        price is.

        Setups are GEOMETRY, not forecasts: an entry is a level cluster, a stop
        is that level offset by a measured multiple of daily range, and
        `rr_ratio` is computed from those prices. `status` is derived per
        request — pending, in_zone or passed.

Input parameters:

- `limit` (integer)
- `symbol` (string, required)

### `get_top_galaxy_scores` (~90 tokens)

Scores · Top by Galaxy Score

The assets with the strongest Galaxy Score right now.

        Galaxy Score is 0-100 and composite: social volume, engagement,
        sentiment and market health folded together. A high score is a
        statement about ATTENTION AND HEALTH, not about valuation — it does not
        mean an asset is cheap. Call get_asset_scores for the breakdown.

Input parameters:

- `limit` (integer)

### `get_top_altranks` (~83 tokens)

Scores · Top by AltRank

The assets ranked best by AltRank right now — relative standing, not absolute.

        AltRank is a RANK: 1 is the strongest in the universe. A rising AltRank
        in a falling market means outperforming the fall, not going up. Pair
        with get_asset_scores when the distinction matters.

Input parameters:

- `limit` (integer)

### `get_correlation` (~86 tokens)

Analytics · Social-price correlation

How closely an asset's social activity tracks its price, with the lead/lag.

        Correlation is not causation and this endpoint does not claim it is. A
        high coefficient says the two series moved together over the window —
        it does not say which one moved first. Use get_leading_indicators for
        that question.

Input parameters:

- `symbol` (string, required)

### `get_leading_indicators` (~91 tokens)

Analytics · Leading indicators

Which social and on-chain signals have historically MOVED FIRST for an asset.

        This is the lead/lag question that get_correlation deliberately does not
        answer. A lead measured over a past window is not a forecast and the
        response does not present it as one — it is the observed ordering of two
        series, and it can break.

Input parameters:

- `symbol` (string, required)

### `get_social_dominance` (~106 tokens)

Social · Share of conversation

Each asset's SHARE of total social attention over a window, with the posts,
        distinct authors, engagement and sentiment behind the share.

        Share is relative and sums across the universe, so an asset's dominance
        can fall while its absolute volume rises — that is the market getting
        louder, not the asset getting quieter. Distinct authors is the column
        that separates a real conversation from one account posting 400 times.

Input parameters:

- `hours` (integer)

### `get_topic_rank` (~99 tokens)

Social · Topic rank

Rank what the market is TALKING ABOUT — themes and narratives, not assets.

        Ranked by mentions weighted by engagement over the window, so a topic
        posted about loudly by few accounts does not outrank one discussed
        widely. Use get_trending_assets for tickers; this is the layer above,
        where "restaking" and "AI agents" live.

Input parameters:

- `hours` (integer)
- `limit` (integer)

### `get_whale_transactions` (~110 tokens)

On-chain · Whale transactions

Recent large on-chain transfers, optionally filtered to one asset.

        "Whale" is a SIZE threshold, not an identity. A large transfer is very
        often an exchange moving its own funds between wallets, which is not a
        market action at all — counterparty labels are included where we hold
        them, and a null label means WE HAVE NO LABEL, never that the
        counterparty is unknown or safe.

Input parameters:

- `limit` (integer)
- `symbol`

### `get_exchange_flows` (~92 tokens)

On-chain · Exchange flows

Net movement of an asset into and out of exchange wallets.

        Inflows are supply arriving somewhere it can be sold; outflows are
        supply leaving to self-custody. The conventional reading is
        distribution vs accumulation, but a single large transfer can be an
        exchange rebalancing its own wallets — check get_entity_flows before
        attributing intent.

Input parameters:

- `symbol`

### `get_aspect_sentiment` (~80 tokens)

Sentiment · By aspect

Split an asset's sentiment by what people are actually talking about:
        technology, price, team and community.

        The aggregate can be flat while the parts disagree sharply — bullish on
        technology, bearish on team is a different situation from uniformly
        neutral, and only this tool can tell them apart.

Input parameters:

- `asset` (string, required)

### `analyze_sentiment` (~96 tokens)

Sentiment · Score arbitrary text

Score any text for crypto sentiment, tuned for crypto slang and tickers.

        Takes arbitrary text you supply — it does not look anything up. General
        sentiment models read "this is going to zero" and "wagmi" badly; this
        one is fitted to the register. Returns polarity plus the terms that
        drove it, so a score can be checked rather than trusted.

Input parameters:

- `text` (string, required)

### `get_influencers` (~88 tokens)

Social · Influencers by asset

The accounts driving conversation about one asset, by reach and engagement.

        Ranked by measured activity in our corpus, NOT by follower count, and
        NOT by whether they were right — see get_influencer_ledger for track
        record. A large account posting noise ranks here; that is the point of
        keeping the two tools separate.

Input parameters:

- `asset` (string, required)

### `get_signal_integrity` (~59 tokens)

Signal integrity · Real-vs-fake score

Get the Signal Integrity score (0-100) — is the move real or exit liquidity?
        Fuses social authenticity + on-chain reality + fundamental backing, with an
        Exit Liquidity Radar flag.

Input parameters:

- `symbol` (string, required)

### `get_influencer_ledger` (~55 tokens)

Influencer ledger · Track record

Get an influencer's accountability record: did their calls precede the move
        (Predictor) or react to it (Reactor)? Includes hit rate and track record.

Input parameters:

- `influencer_id` (string, required)

### `get_influencer_leaderboard` (~82 tokens)

Influencer ledger · Leaderboard

The influencer accountability leaderboard, ranked by what people actually
        got RIGHT rather than by how loud they are.

        Each entry is scored Predictor vs Reactor: did the call come before the
        move, or after it. This is the flagship differentiator — reach and
        accuracy are different axes, and most rankings only publish the first.

### `search_assets` (~59 tokens)

Assets · Search

Search the whole asset universe (~1,900 assets) by symbol or name.
        Use this to resolve a user's loose reference into a real symbol before
        calling the other tools.

Input parameters:

- `limit` (integer)
- `query` (string, required)

### `get_data_coverage` (~61 tokens)

Coverage · Data

What data this platform actually holds right now: asset count, how many
        are priced, chains covered, labelled addresses, social corpus size, and
        freshness timestamps. Call this to check whether an answer is supportable
        before asserting it.

### `get_chain_coverage` (~58 tokens)

Coverage · Chains

Per-chain coverage — tokens mapped, labelled addresses, whale
        transactions seen, and how many were attributed to a named entity.
        Attribution is Etherscan-derived, so it is strong on Ethereum and sparse
        on other chains.

### `get_asset_platforms` (~35 tokens)

Assets · Contract addresses

Every chain an asset is deployed on, with its contract address and
        token decimals.

Input parameters:

- `symbol` (string, required)

### `lookup_address` (~81 tokens)

On-chain · Address lookup

Identify a blockchain address — exchange, bridge, DEX, MEV bot, mining
        pool, or OFAC-sanctioned — with the source and confidence of each label.
        IMPORTANT: `known: false` means no label is held. It does NOT mean the
        address is clean or unflagged.

Input parameters:

- `address` (string, required)

### `list_labelled_addresses` (~72 tokens)

On-chain · Labelled addresses

Browse labelled addresses, filtered by chain, entity (e.g. Binance) or
        category (exchange | bridge | dex | mev | staking | mining | sanctioned).

Input parameters:

- `category` (string)
- `chain` (string)
- `entity` (string)
- `limit` (integer)

### `list_metrics` (~111 tokens)

Metrics · Catalogue

List every metric Onvexia knows, with its parity and caveats.

        parity=exact means we compute it the way Santiment does; approximate means
        same concept but different coverage or method (read the caveat before
        relying on the number); unavailable means we do NOT serve it yet.
        Unavailable metrics are listed on purpose — check here before asserting
        that Onvexia can answer a question.

Input parameters:

- `available_only` (boolean)
- `category` (string)

### `get_metric_metadata` (~91 tokens)

Metrics · Metadata

Describe one metric before you use it: parity, category, minimum interval
        and any caveat attached to it.

        CALL THIS BEFORE get_metric_timeseries if the metric is unfamiliar. The
        minimum interval tells you the finest resolution that is real rather
        than interpolated, and the caveat is where an approximate metric admits
        what it approximates.

Input parameters:

- `metric` (string, required)

### `get_metric_timeseries` (~131 tokens)

Metrics · Timeseries

Timeseries for any available metric on any asset.

        Accepts Santiment-style relative dates ("utc_now-7d") as well as ISO
        timestamps. If the metric is not available this returns an error naming it
        rather than an empty series — an empty result here always means "no data in
        that range", never "we do not have this metric".

Input parameters:

- `aggregation` (string)
- `asset` (string, required)
- `from_date` (string)
- `interval` (string)
- `metric` (string, required)
- `to_date` (string)

### `get_entity_flows` (~49 tokens)

On-chain · Entity flows

Whale flow per labelled entity over the window. Inflow to an exchange
        is distribution pressure; outflow is accumulation.

Input parameters:

- `hours` (integer)
- `limit` (integer)

### `get_metric_timeseries_multi` (~113 tokens)

Metrics · Timeseries (multi-asset)

Timeseries for ONE metric across MANY assets in a single call.

        `assets` is comma-separated (e.g. "BTC,ETH,SOL"). Prefer this over
        looping get_metric_timeseries — it is one round trip instead of N, and
        the values are guaranteed to come from the same read.

Input parameters:

- `assets` (string, required)
- `from_date` (string)
- `interval` (string)
- `metric` (string, required)
- `to_date` (string)

### `get_metrics_batch` (~53 tokens)

Metrics · Batch

Latest value of MANY metrics for ONE asset in a single call.
        `metrics` is comma-separated. The mirror of get_metric_timeseries_multi.

Input parameters:

- `asset` (string, required)
- `metrics` (string, required)

### `screen_assets` (~135 tokens)

Screener · Run screen

Filter the whole asset universe server-side and return the matches.

        `filter` is comma-separated `field:op:value` terms, e.g.
        "market_cap:gt:1000000000,funding_rate:lt:0" — assets over $1B whose
        funding rate is negative. Ops: gt, gte, lt, lte, eq, ne.
        Call screener_fields() first to see what fields exist and their ranges;
        guessing a field name gets the whole query rejected.

Input parameters:

- `filter` (string)
- `limit` (integer)
- `sort` (string)

### `screener_fields` (~35 tokens)

Screener · Available fields

Every field the screener accepts, with type and description. Call this
        before building a filter rather than guessing field names.

### `get_ohlcv` (~91 tokens)

Market · OHLCV

Daily candles (open/high/low/close/volume) for an asset, with the
        venue they came from. Coverage is bounded by which assets have a USDT
        pair on Binance or Bybit — an asset absent here has no candle source we
        collect, which is not the same as having no price.

Input parameters:

- `limit` (integer)
- `symbol` (string)

### `get_trending_assets` (~34 tokens)

Social · Trending assets

Assets trending now by social activity, with the hype score that
        separates a real move from a burst of noise.

### `get_entities` (~52 tokens)

Assets · Entities

Named entities extracted from social documents about an asset —
        people, organisations, products and other tickers mentioned alongside
        it. Use it to find what a narrative is actually about.

Input parameters:

- `asset` (string, required)

### `get_sentiment_trends` (~85 tokens)

Sentiment · Trends

Sentiment over time for an asset, with sample size and confidence
        interval. IMPORTANT: sentiment measured on few documents is unreliable —
        our own bootstrap put the direction wrong 35.6% of the time at n=1 and
        9.5% at n=20. Read n before quoting a direction.

Input parameters:

- `asset` (string, required)

### `get_bot_detections` (~154 tokens)

Signal integrity · Bot detections

Accounts flagged as automated or coordinated, with the behavioural
        evidence. Volume from these should not be read as organic attention.

        READ `coverage` AND `note` BEFORE YOU READ THE LIST. No scorer is
        currently running, so `bot_probability` is NULL for every account and
        this list comes back EMPTY. An empty list here says nothing whatsoever
        about how clean the corpus is — it means nobody has been scored yet,
        and the response says so explicitly in `note`.

        `coverage.accounts_scored` vs `accounts_total` is the honest number:
        while the first is 0, treat this tool as reporting our coverage, not
        the market's cleanliness.

### `get_coordinated_campaigns` (~50 tokens)

Signal integrity · Coordinated campaigns

Detected coordinated posting campaigns — the same message pushed by
        multiple accounts. Matching is exact-text, so this catches copypasta and
        misses the same campaign reworded.

### `get_creator_rankings` (~84 tokens)

Scores · Creator rankings

Rank social creators across the whole corpus by measured influence.

        Corpus-wide, unlike get_influencers which is scoped to one asset.
        Influence is computed from engagement our collectors actually observed,
        so a creator we do not ingest is absent rather than ranked low — an
        absence here is a coverage fact, not a judgement.

Input parameters:

- `limit` (integer)

### `get_asset_revisions` (~59 tokens)

Assets · Revision history

Metrics for this asset that CHANGED after they were first published,
        with the old value, the new one and why. An agent that quoted an earlier
        number can find out here that it moved.

Input parameters:

- `symbol` (string, required)

### `get_trending_stories` (~80 tokens)

Narrative · Trending stories

Current narratives, each an LLM summary of a CLUSTER of posts rather
        than a single document.

        Read author_count before quoting one: a high post_count with a low
        author_count is one person repeating themselves, not a narrative. These
        are machine summaries, not edited articles.

Input parameters:

- `limit` (integer)

### `get_narrative_clusters` (~64 tokens)

Narrative · Clusters

The raw clusters behind the stories, without the prose — for a model
        doing its own summarisation. Every cluster has >= 2 distinct authors;
        near-identical posts from one account are copypasta and excluded.

Input parameters:

- `limit` (integer)

### `list_research_reports` (~74 tokens)

Research · Available reports

List the assets that currently have a generated research report available.

        Returns the index, not the reports — call get_research_report with a
        symbol for the body. An asset missing from this list has not been
        written up; that is a statement about our coverage, not about the
        asset.

### `get_research_report` (~66 tokens)

Research · Report

One asset's generated report. The `unavailable` field lists metrics
        the report could NOT use — read it, because a report that silently omits
        funding rate reads as a report about an asset with unremarkable funding.

Input parameters:

- `symbol` (string, required)

### `resolve_ticker` (~94 tokens)

Assets · Resolve ambiguous ticker

Does a bare ticker actually mean the crypto asset?

        verdict 'crypto' means mentions are about the asset; 'equity'/'other'
        means the bare word is dominated by something else (TIA is Spanish
        'tia'; GRT collides with 'graph'). A 404 is NOT a clean bill of health —
        it means nobody has adjudicated that ticker yet.

Input parameters:

- `ticker` (string, required)

### `get_social_coverage` (~80 tokens)

Coverage · Social

How many assets actually clear the document floor that makes each
        social metric computable.

        Call this BEFORE quoting sentiment for an asset. A large corpus total
        does not mean sentiment works everywhere: attention is a power law and
        the documents pile onto BTC, so most assets stay uncomputable.

Input parameters:

- `band` (integer)

### `list_nl_screens` (~59 tokens)

Screener · Saved natural-language screens

Previously compiled natural-language screens: the English somebody
        wrote and the filter it compiled to, INCLUDING refusals. Useful as
        worked examples of the screener's filter grammar before you write one.

Input parameters:

- `limit` (integer)

### `get_agent_findings` (~67 tokens)

Agents · Findings

What this platform's own monitoring agents are currently complaining
        about — dead collectors, stale data streams, coverage drops.

        Worth checking before relying on a number: a stream flagged stale here
        is still being served, it is just old.

Input parameters:

- `limit` (integer)

### `run_sql` (~58 tokens)

SQL · Run read-only query

Run a read-only SELECT against the platform's data. One statement, 15s timeout, 10,000-row cap; truncation is always reported. Call get_sql_schema first for the queryable relations.

Input parameters:

- `query` (string, required)

### `get_sql_schema` (~30 tokens)

SQL · Schema

List every relation and column queryable via run_sql, plus the rules and what is deliberately not exposed.

### `get_hodl_waves` (~37 tokens)

On-chain · HODL waves

Bitcoin supply split by coin age over time — which cohorts are holding and which are moving.

Input parameters:

- `limit` (integer)

### `get_exchange_netflow` (~46 tokens)

On-chain · Exchange netflow

Per-token flow onto and off exchanges. Inflow is distribution pressure, outflow is accumulation. net_usd where the token can be priced.

Input parameters:

- `limit` (integer)

### `get_constellation` (~34 tokens)

On-chain · Entity graph

Asset co-mention graph — which assets are discussed together, with what was filtered out.

Input parameters:

- `limit` (integer)

### `get_social_posts` (~53 tokens)

Social · Posts

Collected social posts, optionally filtered by platform (bluesky, farcaster, reddit, 4chan, bitcointalk, rss).

Input parameters:

- `limit` (integer)
- `platform` (string)

### `get_similar_posts` (~56 tokens)

Social · Similar posts

Posts nearest a given post in embedding space. Read the returned BAND, never the raw cosine — 43% of this corpus sits at 0.80-0.90 by default.

Input parameters:

- `post_id` (integer, required)

### `get_asset_social_signal` (~44 tokens)

Social · Asset signal

Per-asset social signal over time. The `available` field states plainly whether we hold it.

Input parameters:

- `days` (integer)
- `symbol` (string, required)

### `get_metric_revisions` (~42 tokens)

Metrics · Revisions

Restatements of published numbers — what changed, over which period, and why. A correction is not a market move.

Input parameters:

- `limit` (integer)

### `get_emerging_dex_pairs` (~98 tokens)

Market · Emerging DEX pairs

Newly created DEX pairs above a USD liquidity floor.

        THE FLOOR IS RETURNED IN THE RESPONSE, and it is load-bearing: this is
        the long tail where most pairs are rugs or noise, and the floor is the
        only thing separating a signal from a list of scams. Raising it shrinks
        the result set and raises its quality.

Input parameters:

- `min_liquidity_usd` (integer)

### `get_exchange_listings` (~77 tokens)

Market · Exchange listings

Recent exchange listing announcements — an asset being added to a venue.

        A listing is an ATTENTION event, not a fundamental one: it changes who
        can buy, not what the project is worth. Use it to explain a volume or
        social spike, not as a valuation input.

Input parameters:

- `limit` (integer)

### `get_address_coverage` (~35 tokens)

Coverage · Addresses

What we index per chain for watched addresses: what we see, what we miss, and what an empty feed actually means.

### `get_address_events` (~46 tokens)

On-chain · Address events

Events on watched addresses. Check get_address_coverage before reading an empty result as silence — below the observed USD floor, movement is invisible to us.

Input parameters:

- `limit` (integer)

### `get_story_posts` (~73 tokens)

Narrative · Story sources

The individual posts a story was assembled from — the receipts.

        Call this whenever a story matters enough to check. A generated story is
        a summary over these posts; this is how you verify it says what the
        sources say rather than taking the summary on trust.

Input parameters:

- `story_id` (integer, required)

### `get_narrative_rotation` (~234 tokens)

Narrative · Rotation

Which crypto narrative is GAINING or LOSING attention share, with a
        liquidity confirmation leg.

        Compares the last `days` against the equally long window immediately
        before. Covers the 2026 narrative set — RWA, tokenized equities and
        treasuries, stablecoins, DePIN, perp DEXs, prediction markets, AI agents
        — as well as DeFi, NFT, Gaming and the L1/L2 split.

        READ `vocabulary_stale` BEFORE QUOTING ANY DELTA. When true, the corpus
        spans two keyword vocabularies and a narrative whose keywords were just
        added will appear to be rising purely because only recent posts were
        ever tested against them. That is a rotation signal manufactured by a
        deploy, not by the market.

        A narrative with `unconfirmed: true` has measured attention and NO
        liquidity confirmation — the confirmation is absent, not zero, and the
        row states why.

Input parameters:

- `days` (integer)
- `include_legacy` (boolean)

### `get_ai_substance` (~189 tokens)

Signal integrity · AI substance

Does an AI-sector project actually ship code, against how much
        attention it gets.

        Four states, and the fourth is not a verdict:
          ships           public repo with development activity in 30 days
          silent          public repo, no activity in 30 days
          no_public_repo  no repository is published for this asset
          unmapped        WE have not checked. This is a gap in OUR coverage
                          and must NEVER be reported as the project failing to
                          ship. RENDER sat in this state with 447 posts while
                          publishing code the whole time.

        `dev_events_30d` is null rather than 0 for the last two states: there is
        no repository to have produced a zero. `attention_without_substance` is
        only ever set where the state was actually measured.

Input parameters:

- `limit` (integer)

### `get_wrapper_basis` (~162 tokens)

Market · Wrapper basis

Cross-wrapper spread for tokenized equities: one real company, every
        issuer that tokenizes it, and how far apart they trade.

        SpaceX trades under five wrappers and they do not agree. Spreads run
        roughly 0.1-0.9 percent between programs referencing the same share.

        This is a CROSS-WRAPPER comparison, deliberately not a comparison
        against the underlying stock — that needs a licensed equity feed and no
        free commercially-usable one exists.

        A spread is NOT free money. Each issuer carries its own credit,
        redemption terms and transfer restrictions, and the cheapest wrapper is
        often cheapest for a reason. Do not present it as an arbitrage.

Input parameters:

- `limit` (integer)

### `get_disclosures` (~235 tokens)

Fundamentals · Public disclosures

Public-record documents about issuers we track: SEC filings and
        federal court dockets.

        Exists because both RWA failures of 2026 were disclosed in public text
        before the price moved -- RealT's tax delinquency sat in court filings
        for a year, Goldfinch's borrower defaults were in governance forums
        before the vote.

        TWO THINGS YOU MUST NOT MISREPORT:

        A null `severity` means the document was FOUND and NOT ASSESSED. It is
        unjudged, not benign, and must never be summarised as "nothing
        concerning".

        `match_confidence: name_unverified` means the document was matched on a
        NAME and may concern a different company entirely -- searching for
        'RealT' returns 'Broadway White Realty'. Do not attribute an unverified
        filing to an issuer without checking it.

        An empty result means nothing has been found, which for a subject never
        searched is not a statement about them at all.

Input parameters:

- `limit` (integer)
- `symbol` (string)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-onvexia-onvexia/onvexia#diagnostics

## Score history

- 2026-09-20: 73
- 2026-09-19: 72
- 2026-09-18: 72
- 2026-09-17: 71
- 2026-09-16: 71

## Common questions

### What is the Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking MCP server?

Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking is an MCP server listed in the public MCP registry as com.onvexia/onvexia. Crypto fundamental analysis, sentiment and whale tracking for traders and AI agents. This page covers its hosted endpoint (https://onvexia.com/mcp).

### Is the Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking MCP server safe to use?

Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking scores 73 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 Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking MCP server expose?

Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking exposes 66 tools: get_asset, get_asset_scores, get_asset_fundamentals, get_asset_technicals, get_top_galaxy_scores, and 61 more. Their descriptions and schemas cost roughly 5,644 tokens of context every time the server is loaded.

### Does the Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking MCP server require authentication?

No. We connected to Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking MCP server still maintained?

Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking 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.

## Links

- Remote endpoint: https://onvexia.com/mcp
- Repository: https://github.com/faraz152/onvexia-mcp
- Website: https://onvexia.com/
- Changelog RSS feed: https://verifymcp.io/servers/com-onvexia-onvexia/onvexia.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-onvexia-onvexia/onvexia.json
- HTML version of this page: https://verifymcp.io/servers/com-onvexia-onvexia/onvexia