ProfitSpot MCP — The DeFi Brain for AI Agents
PYPI · PROFITSPOT-MCP · 2 COMPONENTS · SCANNED SEP 20
Claude-ready DeFi MCP — risk-scored yields, profit sims & whale tracking across 86 blockchains
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 Security50
- Malware scan not yet available for this package.Unverified
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 1 of 24 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency19
- Repository check failed: no source repository is declared. See how to fix → View diagnostics → Fail
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (AGPL-3.0-or-later).Pass
- Actively maintained (last published 147 days ago).Pass
- Security-disclosure policy not yet verified: we couldn't inspect the source repository.Unverified
Schema Quality & AI Usability67
- AI-judged instruction clarity (good).Pass
- Context-footprint check failed: tool/resource definitions use about 862 tokens (~123/item across 7 items; 7 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 Management80
- Stability observed for 24 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 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
- 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 7 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 current MCP spec version (2026-07-28).Pass
How do I install the ProfitSpot MCP — The DeFi Brain for AI Agents server?
ProfitSpot MCP — The DeFi Brain for AI Agents runs locally as a PyPI package, launched with uvx profitspot-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · profitspot-mcp
claude mcp add omniologynow-rgb-profitspot-mcp -- uvx profitspot-mcp
{
"mcpServers": {
"omniologynow-rgb-profitspot-mcp": {
"command": "uvx",
"args": [
"profitspot-mcp"
]
}
}
} {
"servers": {
"omniologynow-rgb-profitspot-mcp": {
"command": "uvx",
"args": [
"profitspot-mcp"
]
}
}
} codex mcp add omniologynow-rgb-profitspot-mcp -- uvx profitspot-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"omniologynow-rgb-profitspot-mcp": {
"type": "local",
"command": [
"uvx",
"profitspot-mcp"
],
"enabled": true
}
}
} openclaw mcp add omniologynow-rgb-profitspot-mcp --command uvx --arg profitspot-mcp
mcp_servers:
omniologynow-rgb-profitspot-mcp:
command: "uvx"
args: ["profitspot-mcp"] {
"McpServers": {
"omniologynow-rgb-profitspot-mcp": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"profitspot-mcp"
]
}
}
} assistant mcp add omniologynow-rgb-profitspot-mcp -t stdio -c uvx -a profitspot-mcp
{
"mcpServers": {
"omniologynow-rgb-profitspot-mcp": {
"command": "uvx",
"args": [
"profitspot-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.
- 20 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 77 to 80. That category is still filling its 30-day observation window: 23 days of observed history at the previous scan, 24 at this one. The score rises as the window fills, whether or not the server changes.
- 19 Sept 26 −4
- Stability: pass → 0.77 functional
- 18 Sept 26 +1
- Stability: 0.97 → pass security
- 16 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.
- 14 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.
- 12 Sept 26 −3
- Stability: pass → 0.80 functional
- 11 Sept 26 +1
- Stability: 0.97 → pass security
- 9 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.
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 pypi/profitspot-mcp@1.1.2
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 24 packages
| Packages resolved | 24 |
|---|---|
| Stale | 1 |
| 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 →
analyze_pool Analyze Pool ~106
Deep analysis of a specific DeFi pool. Returns: full pool data, historical APY trends (7d/30d/90d), TVL history, risk grade with full breakdown (why it got that grade), IL estimate scenarios for LP pools, and projected returns at current APY for $1K/$10K/$100K over 30/90/365 days. PRO ONLY — requires PROFITSPOT_API_KEY.
| Name | Type | Req | Description |
|---|---|---|---|
| pool_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
calculate_impermanent_loss Calculate Impermanent Loss ~119
Calculate exact impermanent loss for a 50/50 LP pair. Given price change percentages for both tokens, calculates exact IL in USD and percentage. Also returns: value if held vs value in LP, and net gain/loss including trading fees at various APY levels (5%, 10%, 20%, 50%). ALWAYS FREE — pure math, no API call needed.
| Name | Type | Req | Description |
|---|---|---|---|
| investment_amount | number | – | – |
| token_a_price_change | number | yes | – |
| token_b_price_change | number | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
defi_overview Defi Overview ~94
Big-picture DeFi dashboard. Returns: total DeFi TVL, TVL by top 10 chains, top 10 protocols by TVL, pool counts, and average yields. FREE tier: basic stats (TVL, chains, protocols). PRO tier: + average yields by risk grade, stablecoin market cap, hot opportunities (new pools with high APY + good risk grade).
| Name | Type | Req | Description |
|---|---|---|---|
| chain | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
discover_yields Discover Yields ~144
Discover top DeFi yield opportunities across 86 chains and 6,500+ pools. Filter by chain, minimum TVL, minimum APY, and maximum risk grade (A-F). Returns sorted list with pool name, protocol, chain, APY, TVL, risk grade, prediction (stable/up/down), and stablecoin flag. FREE tier: limited to 10 results, no risk filtering. PRO tier: up to 50 results with full risk grade filtering.
| Name | Type | Req | Description |
|---|---|---|---|
| chain | – | – | – |
| limit | integer | – | – |
| max_risk | string | – | – |
| min_apy | number | – | – |
| min_tvl | number | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
risk_score Risk Score ~101
Get risk grade (A-F) for a specific pool or entire protocol. Returns overall grade, breakdown scores for: TVL stability, APY sustainability + volatility, protocol reputation + age, IL exposure, pair stability, and security/audit proxy. Each sub-score explained in plain English. For protocols: scores the top pools and returns an aggregate grade. PRO ONLY — requires PROFITSPOT_API_KEY.
| Name | Type | Req | Description |
|---|---|---|---|
| pool_id | – | – | – |
| protocol | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
simulate_profit Simulate Profit ~129
Project returns for a specific pool using Monte Carlo simulation. Uses Ornstein-Uhlenbeck APY model that accounts for: APY mean reversion, APY crash events, impermanent loss via geometric Brownian motion, pool failure probability, and gas costs. Runs 1,000 simulations. Returns optimistic/base/bearish scenarios with dollar amounts, percentiles, probability of profit, and risk factors. PRO ONLY — requires PROFITSPOT_API_KEY.
| Name | Type | Req | Description |
|---|---|---|---|
| compound | boolean | – | – |
| days | integer | – | – |
| investment | number | – | – |
| pool_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
track_whales Track Whales ~124
Detect large capital movements (whale activity) across DeFi pools. Finds pools where TVL changed by >$500K since last snapshot. Reports: pool, direction (inflow/outflow), amount, percentage change, and whether this correlates with APY changes. First call establishes a baseline; subsequent calls detect actual changes. Also uses APY-change heuristics as a proxy for whale activity. PRO ONLY — requires PROFITSPOT_API_KEY.
| Name | Type | Req | Description |
|---|---|---|---|
| chain | – | – | – |
| min_tvl_change | number | – | – |
| timeframe | string | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
What is the ProfitSpot MCP — The DeFi Brain for AI Agents server?
ProfitSpot MCP — The DeFi Brain for AI Agents is listed in the public MCP registry as io.github.omniologynow-rgb/profitspot-mcp. Claude-ready DeFi MCP, risk-scored yields, profit sims & whale tracking across 86 blockchains. This page covers its PyPI package (profitspot-mcp).
Is the ProfitSpot MCP — The DeFi Brain for AI Agents server safe to use?
ProfitSpot MCP — The DeFi Brain for AI Agents scores 58 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. 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 ProfitSpot MCP — The DeFi Brain for AI Agents server expose?
ProfitSpot MCP — The DeFi Brain for AI Agents exposes 7 tools: discover_yields, analyze_pool, calculate_impermanent_loss, simulate_profit, risk_score, and 2 more. Their descriptions and schemas cost roughly 817 tokens of context every time the server is loaded.
Is the ProfitSpot MCP — The DeFi Brain for AI Agents server still maintained?
ProfitSpot MCP — The DeFi Brain for AI Agents 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 ProfitSpot MCP — The DeFi Brain for AI Agents server under?
ProfitSpot MCP — The DeFi Brain for AI Agents declares the AGPL-3.0-or-later licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.