AskTony is a real-time intelligence platform that delivers instant context across your entire engineering stack. It connects Sentry, Slack, Jira, GitHub, and Notion to help engineering teams find answers in under 2 seconds without switching tabs.

How does AskTony provide real-time intelligence?

AskTony uses webhooks to receive instant notifications when errors occur in Sentry, commits merge in GitHub, tickets update in Jira, or docs change in Notion. This data is immediately indexed using vector embeddings, ensuring answers reflect your stack's current state—not yesterday's.

What makes AskTony different from ChatGPT or GitHub Copilot?

ChatGPT and Copilot are trained on public data. AskTony is trained on YOUR stack—your private code, docs, tickets, and conversations. It connects related events across tools (e.g., 'This Sentry error relates to commit xyz mentioned in Slack thread abc'). Plus, it's proactive with a live activity feed, not just reactive Q&A.

How fast does AskTony respond?

AskTony delivers answers in under 1.2 seconds (Time to First Token). It uses parallel vector search across all connected tools and optimized inference pipelines to ensure developers get instant context without waiting.

Yes. AskTony uses OAuth for read-only access to your tools. Data is encrypted in transit and at rest, stored in isolated databases per organization, and never shared outside your team. You control which repos, channels, and docs Tony can access.

Can AskTony access my private code and data?

Yes, with your explicit authorization. AskTony uses OAuth for read-only access. You choose which repositories, Slack channels, Jira projects, and Notion pages Tony can access. Data is encrypted and isolated per organization.

How do I get started with AskTony?

Visit app.asktony.dev, sign up with your work email, and authorize Tony to access your tools (Sentry, Slack, Jira, GitHub, Notion). Initial setup takes 5 minutes. Tony will index your data and be ready to answer questions in under 10 minutes.

Does AskTony work for small teams?

Absolutely. AskTony is built for teams of 5-12 engineers. Small teams benefit from faster onboarding and less context switching. Larger teams benefit from cross-teams visibility and institutional knowledge retention.

What is the live activity feed?

The live activity feed is a real-time stream showing what's happening across your stack—new Sentry errors, GitHub commits, Jira ticket updates, Slack mentions, and Notion doc changes. It keeps you proactively informed without checking multiple tools.

How does role-based intelligence work?

AskTony adapts answers based on your role (Developer, QA, Product Manager, Engineering Manager). The same question gets different depth and focus—developers see code and commits, QA sees test coverage and bugs, PMs see impact and timelines.

What happens if AskTony doesn't know the answer?

AskTony will tell you it doesn't have enough context and suggest which tools to connect or which data sources to authorize. It never makes up answers—if the information isn't in your connected tools, Tony will be honest about it.

Can I use AskTony for incident response?

Yes. AskTony excels at incident response by instantly connecting Sentry errors with recent commits, related Slack discussions, and open Jira tickets. Instead of manually correlating data across tools, ask 'What caused the prod outage?' and get a unified answer in seconds.

How does AskTony help with onboarding?

New team members can ask questions like 'How does our auth flow work?' and get answers synthesized from code, documentation, and past Slack conversations. This reduces onboarding time from weeks to days by making institutional knowledge instantly accessible.

Does AskTony replace my existing tools?

No. AskTony is an intelligence layer on top of your existing tools. You still use Sentry for error monitoring, Slack for communication, Jira for project management, GitHub for code, and Notion for docs. Tony just makes it faster to find information across all of them.

AskTony offers a free demo with 10 questions per session. Paid plans start at a per-user monthly rate for teams. Contact us at app.asktony.dev for custom enterprise pricing and dedicated support.

What is Model Context Protocol (MCP)?

Model Context Protocol (MCP) is an open standard for connecting AI systems with external data sources and tools. AskTony is built on MCP, allowing it to seamlessly integrate with Sentry, Slack, Jira, GitHub, and Notion through standardized MCP servers.

How does AskTony use MCP?

AskTony uses MCP servers to connect with your engineering tools. Each integration (Sentry, Slack, Jira, GitHub, Notion) runs as an MCP server, providing a standardized interface for real-time data sync, webhook handling, and semantic search. This makes AskTony extensible and easy to maintain.

Can I add custom MCP integrations to AskTony?

Yes. Since AskTony is built on Model Context Protocol, you can add custom MCP servers for any tool your team uses. The MCP architecture ensures seamless integration without modifying AskTony's core code.

AskTony - Real-time Intelligence Across Your Stack | MCP-Based Engineering Assistant

TONY

Project knowledge assistant

Tony pulls the Sentry spike, the commit, and the ticket — with the file and line you’ll need at 1 AM.

Real-time intelligence across your stack.

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Reasons

3 core capabilities that make Tony, the essential teammate of engineering teams.

Onboarding, on steroids

New engineers get instant context on code, docs and logs. Tony helps cut ramp-up time by weeks.

Role based intelligence

Same question, different lens — code context for devs, test insights for QA, impact analysis for PMs.

Root Cause Analysis, like never before

Tony ties logs to commits and deployments — showing the “why” and the next steps in seconds.

Real-time intelligence across your stack.

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Tony keeps an eye out

Anomaly detection

Out-of-pattern spikes tied to commits and tickets.

Release readiness

Open bugs, flaky tests, last 24h changes — go/no-go.

Historical context

Today's events tied to past decisions.

Peek into our live feed

MCP powered Integrations

Connect your tools with live data sync. No more stale wikis or manual updates.

GitHub

GitLab

Confluence

Jira

Figma

Grafana

Elastic

Kafka

Privacy & Security First

Your source code never leaves your infrastructure in readable form

Enterprise Encryption

Authentication

VPN Access

Private LLM

Full Compliance

Data Residency

Everything is converted to encrypted vectors with VPN-only access. Integrate with your existing project tools, thanks to the simplicity of MCP Servers.

No code scanning, no data mining, no external processing of sensitive information.

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Frequently Asked Questions

What is AskTony?

AskTony is your team's proactive knowledge assistant. It connects to your engineering tools — tracking changes in real-time and helping you solve problems faster.

Is AskTony secure?

Yes. AskTony integrates with your existing authentication, VPN and access controls, so only authorized users can access sensitive information. Data is never shared outside the team.

How is Tony different from ChatGPT or GitHub Copilot?

ChatGPT doesn't know your codebase. Copilot doesn't see your Jira tickets or Sentry errors. Tony connects everything — live data from all your tools, with role-based answers for Managers, Devs, and QA.

How does AskTony actually work?

AskTony consolidates your team's knowledge by connecting to your existing tools. It converts them into a strategic vector database. Using a combination of RAG, MCP, Semantic Search, and LLMs, Tony provides accurate and relevant answers to your queries.

How does AskTony keep information fresh?

AskTony uses the Model Context Protocol (MCP) to sync live data from your code repositories, documentation, and incident management tools, ensuring your knowledge base is always current and searchable.

Which tools does AskTony integrate with?

AskTony connects with GitHub, GitLab, Confluence, Jira, Figma, Grafana, Elastic, Kafka, and more. New integrations are added regularly based on customer feedback.

Vision

Today

Real-time awareness with proactive suggestions

Future

Autonomous actions with human in the loop

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