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One MCP connection. Full Convex context. No more console diving — just ask.
Stop opening the Convex dashboard to inspect table data and function logs. Ask your AI agent to query your Convex database, inspect document structures, analyze function execution patterns, and surface data insights — all in plain language.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Run Convex mutations, trigger scheduled functions, update documents, and manage data — all through natural language. Handle one-off data operations and administrative tasks without writing queries in the dashboard.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Set AI-powered watches on function error rates, data growth patterns, and scheduled job health. Get alerts before a silent Convex mutation failure cascades into a user-facing bug.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Run Convex mutations, trigger scheduled functions, update documents, and manage data — all through natural language. Handle one-off data operations and administrative tasks without writing queries in the dashboard.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
When something goes wrong in a Convex-backed application, developers need to inspect production data to understand the state. This requires direct console access to the Convex dashboard — which not everyone on the team has, and which requires knowing the exact table structure and query syntax to navigate. Non-technical stakeholders asking 'how many users are affected?' have no self-service option.
Your AI agent gives everyone natural language access to Convex production data — without console credentials. Ask any question about the data, and the agent translates it into the appropriate Convex query, executes it safely, and returns a plain-language answer with the relevant documents.
Convex scheduled functions — nightly cleanups, weekly digests, data sync jobs — can fail silently if there's no monitoring in place. The first sign of failure is often a user complaint: 'I didn't get my weekly summary email' or 'the old data is still showing.' By the time it's caught, multiple scheduled runs may have been missed, requiring a manual backfill.
Improvado MCP monitors your Convex scheduled function execution automatically. Your AI agent checks each scheduled job's last execution time and status, flags missed runs, and can trigger a manual execution to catch up — turning reactive incident response into proactive monitoring.
Convex's document-based model allows flexible schemas, but this flexibility creates a common problem: old documents don't automatically get new fields added in newer versions. Over time, the same collection accumulates documents with different field sets — some with the new 'tier' field, some without. Queries that assume all documents have the same shape return inconsistent results, and debugging requires manually sampling documents across time ranges.
Ask your AI agent to audit Convex table schema consistency. It samples documents across creation date ranges, identifies missing or mismatched fields, and returns a report of which documents need migration — before inconsistency causes a production issue.
Same MCP connection, different workflows for every team member. Agency CEOs get portfolio health. Media Strategists get campaign QA. Analysts get cross-platform reports. Account Managers get auto-generated QBR decks. Creative Directors get performance-based briefs.
Each role asks in natural language. The MCP server handles the complexity — rate limits, auth, schema normalization, governance — behind the scenes.
Convex MCP is a Model Context Protocol server that connects your Convex backend to AI agents like Claude, ChatGPT, and Gemini. It lets you query database tables, run functions, inspect document structures, and monitor scheduled jobs — all in natural language, without opening the Convex dashboard.
All tables and documents in your Convex database (subject to your API key permissions), function definitions and execution history, scheduled function status, error logs, and usage metrics. The AI agent can query any table and run read queries or mutations.
Both. Read operations include querying tables, sampling documents, and inspecting function behavior. Write operations include running mutations to update documents, triggering scheduled functions manually, and creating new documents. All write operations require an API key with mutation permissions.
Yes, with appropriate safeguards. Improvado recommends using a read-only API key for query-only use cases. For mutation access, all write operations are explicitly confirmed before execution. The MCP server does not execute mutations automatically without a clear write instruction in your prompt.
Yes. Improvado stores Convex API keys in an encrypted vault certified to SOC 2 Type II. The AI agent never accesses credentials directly. All requests are proxied through Improvado's secure layer.
Under 60 seconds. Generate a Convex API key from your deployment settings, add the MCP server URL to your AI agent config, and you're ready to query. No additional configuration is required for read-only access.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
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