---

name: pond3r-skill description: Query crypto intelligence via Pond3r MCP — curated datasets, SQL queries, protocol metrics, yields, and market analysis. Use when the agent needs DeFi data, stablecoin yields, token opportunities, Polymarket trades, cross-protocol comparisons, or blockchain analytics.

Pond3r Crypto Intelligence Skill

Use this skill when the agent needs to query crypto/DeFi data: yields, protocol metrics, token opportunities, market analysis, or blockchain analytics. Pond3r provides an MCP server with read-only SQL access to curated datasets.

Prerequisites

• API key: Obtain at makeit.pond3r.xyz/api-keys
• MCP setup: Pond3r must be configured as an MCP server in the runtime (Claude Code, Cursor, Claude Desktop, etc.)

Setup: Where Is the Agent Running?

The agent needs MCP tools (list_datasets, get_schema, query) to use Pond3r. Those tools come from the runtime that executes the agent — not from the skill or env vars alone.

Runtime	How to enable Pond3r
Cursor	Cursor Settings → MCP Servers → Add server (URL + Authorization header). See MCP Connection below.
Claude Desktop	Add Pond3r to claude_desktop_config.json under mcpServers. Restart Claude.
Claude Code	Run claude mcp add pond3r-data ... (see below).
OpenClaw (Docker/Telegram)	Use the CLI scripts below. They call Pond3r MCP via HTTP. Set POND3R_API_KEY in .env; the agent runs the scripts and parses JSON output.

No extra info for the agent — the skill is enough. For runtimes with native MCP, add the API key in the MCP server config. For OpenClaw, use the scripts and POND3R_API_KEY in env.

MCP Connection

Setting	Value
URL	https://mcp.pond3r.xyz/mcp
Transport	Streamable HTTP
Auth	Authorization: Bearer <API_KEY>

Cursor

1. Open Cursor → Settings (⌘+,) → MCP
2. Click Add new MCP server
3. Configure:
   • URL: https://mcp.pond3r.xyz/mcp
   • Headers: Authorization: Bearer <YOUR_POND3R_API_KEY>
     • Replace <YOUR_POND3R_API_KEY> with your key from makeit.pond3r.xyz/api-keys
     • Some clients support Authorization: Bearer ${POND3R_API_KEY} if that env var is set
4. Save and restart Cursor so tools load
5. Verify: start a new chat and ask for stablecoin yields — the agent should call list_datasets, get_schema, query

Claude Code

claude mcp add pond3r-data \
  --transport http \
  https://mcp.pond3r.xyz/mcp \
  --header "Authorization: Bearer <API_KEY>"

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "pond3r": {
      "type": "http",
      "url": "https://mcp.pond3r.xyz/mcp",
      "headers": {
        "Authorization": "Bearer <API_KEY>"
      }
    }
  }
}

CLI Scripts (OpenClaw / Any Runtime)

When MCP tools are not available (e.g. OpenClaw/Telegram), use these scripts. They call Pond3r MCP over HTTP. Requires POND3R_API_KEY in env (e.g. in .env loaded by docker-compose).

Scripts live at /opt/pond3r-skill-scripts/ in the Docker image. When running locally, use ceo-agent/skills/pond3r-skill/scripts/ or the workspace-relative path.

1) List datasets

node /opt/pond3r-skill-scripts/list-datasets.mjs

Output: JSON with all datasets and tables.

2) Get schema for a dataset

node /opt/pond3r-skill-scripts/get-schema.mjs --dataset-id <dataset_id>

3) Run a SQL query

node /opt/pond3r-skill-scripts/query.mjs --dataset-id <dataset_id> --sql "SELECT * FROM stablecoin_yields LIMIT 10"

Or from file:

node /opt/pond3r-skill-scripts/query.mjs --sql-file /tmp/query.sql

Script workflow

1. Run list-datasets.mjs to discover datasets and table names.
2. Run get-schema.mjs --dataset-id <id> to see columns and types.
3. Run query.mjs --dataset-id <id> --sql "SELECT ..." with valid SQL (SELECT only, bare table names, LIMIT where appropriate).
4. Parse the JSON output and summarize for the user.

Failure handling

• Missing required env var: POND3R_API_KEY → Add POND3R_API_KEY to .env and ensure it is loaded (e.g. docker-compose env_file: .env).
• Pond3r MCP HTTP 401 → Invalid or expired API key; rotate key at makeit.pond3r.xyz/api-keys.
• Pond3r MCP error: ... → Check SQL syntax, table names, and row limits.

Available Tools (Native MCP)

Tool	Purpose
list_datasets	List all datasets and their tables
get_schema	Get column names, types, descriptions for a dataset
query	Execute read-only SQL against a dataset

Query Rules

• SELECT only — write operations are not allowed
• Bare table names — use SELECT * FROM stablecoin_yields, not fully qualified paths
• Results capped at 10,000 rows — use LIMIT or WHERE filters for large datasets
• Cost estimation — queries exceeding tier limits are rejected before running

Use Cases

1. Protocol Intelligence

   • Track AI agent launches, token graduations, protocol metrics
   • Daily yield farming reports across Aave, Compound, Convex

2. Market Opportunity Detection

   • New tokens on Uniswap with rising liquidity
   • Tokens with <$500K market cap and rising liquidity
   • Polymarket trades with highest volume

3. Risk-Adjusted Analysis

   • Multi-dimensional risk scoring (volatility, liquidity, market structure)
   • Liquidation risk monitoring for DeFi positions
   • Whale activity tracking

4. Cross-Protocol & Cross-Chain

   • Compare USDC yields across Aave and Compound on Arbitrum
   • Bridge volume analysis, ecosystem health comparison
   • Arbitrage opportunity detection

5. Structured Data for Decisions

   • Statistical analysis, trend identification
   • Volume pattern analysis, unusual trading activity
   • Sentiment scoring (Farcaster, influencer activity)

Example Queries (Natural Language → SQL)

Agent asks in natural language; MCP tools discover schema and execute SQL. Example prompts:

• "What are the top 5 stablecoin yields on Ethereum right now?"
• "Show me Polymarket trades from the last 24 hours with the highest volume."
• "Compare USDC yields across Aave and Compound on Arbitrum."

Workflow

1. Discover available data: Call list_datasets to see datasets and tables
2. Understand schema: Call get_schema for the dataset you need
3. Write and run: Use query with valid SQL (SELECT, bare table names, LIMIT where appropriate)
4. Interpret results: Use returned data for analysis, proposals, or decisions

Runtime Enforcement (Mandatory)

Before answering with Pond3r-backed data:

1. Prefer scripts when MCP tools are unavailable:
   • If list_datasets, get_schema, query are not exposed by the runtime, use the CLI scripts instead.
   • Run node /opt/pond3r-skill-scripts/list-datasets.mjs (or workspace path) with POND3R_API_KEY in env.
2. If neither MCP nor scripts work:
   • Stop and return: Pond3r unavailable: MCP tools missing and scripts failed (check POND3R_API_KEY in env).
3. Do not assume fallback permission:
   • Do not switch to web_search, web_fetch, or other sources unless the user explicitly approves fallback.
4. Return execution evidence:
   • Include the exact commands run and summarize returned dataset/query output.
   • If a call fails, include the exact error message and next remediation step.

Troubleshooting

Symptom	Fix
"Pond3r MCP not configured"	Add MCP server in your runtime (Cursor/Claude) with URL + Bearer header. Restart.
Tools still missing after config	Restart the app (Cursor/Claude). MCP loads at startup.
Agent runs in OpenClaw/Telegram	Use the CLI scripts with POND3R_API_KEY in .env. See CLI Scripts.
Auth/401 errors	Check API key is valid, not expired. Rotate if it was ever exposed.

Failure Handling

• If MCP tools are unavailable, provide only:
  • missing tool names
  • required server URL (https://mcp.pond3r.xyz/mcp)
  • required auth header format (Authorization: Bearer <API_KEY>)
• If SQL is rejected (tier/cost/limits), rewrite with tighter WHERE/LIMIT and retry.
• If access/auth fails, report authorization/configuration failure and request key/server verification.

Report API (Alternative to MCP)

For scheduled reports and structured JSON delivery, use the REST API:

• Create report: POST https://api.pond3r.xyz/v1/api/reports with description, schedule, delivery_format
• Get latest: GET https://api.pond3r.xyz/v1/api/reports/{reportId}/latest
• Headers: x-api-key: <API_KEY>

Report format includes executiveSummary, analysis, opportunities. For full API details and response structure, see reference.md.

Security

• Never expose API keys in client-side code or public repositories
• Use environment variables for API keys
• MCP tools are read-only; no writes to Pond3r datasets
• Never print secret values in logs, chat, or command output (only report presence/absence)
• If a secret is accidentally exposed, instruct immediate key rotation before continuing