AI agents can answer “Is there a power cut near me?” more reliably when they can query current utility data instead of relying on static web pages or outdated training data. For Hyderabad, a WebMCP-based integration can expose a controlled outage lookup tool to an agent, resolve a user’s location, fetch information from the relevant electricity provider, and return a timestamped result with clear uncertainty.
WebMCP should be treated as a tool-access and orchestration layer—not as a replacement for an official utility API. The production design must account for Hyderabad’s multiple service areas, Telugu and English addresses, ward or feeder boundaries, authentication, rate limits, stale data, and safe handling of location information.
What WebMCP means for real-time outage agents
WebMCP is best understood as a standardised way for websites and web applications to expose structured capabilities to AI agents. Instead of asking an agent to scrape a page and guess which fields contain outage information, a site can publish a tool with a defined name, input schema, output schema, permissions, and error behaviour.
For a power-outage assistant, the exposed capability might be:
get_power_outage_statusfind_service_areaget_restoration_updatesreport_power_issue
The agent can discover or invoke the permitted operation, provide validated inputs, and receive machine-readable data. The utility remains the source of truth; WebMCP provides a safer interface for agent interaction.
A typical request flow is:
1. The user asks about an outage in Hyderabad.
2. The agent requests a neighbourhood, landmark, address, or optional coordinates.
3. A geocoding or service-area tool maps the location to the correct utility region.
4. The outage tool queries the official status system.
5. The agent validates freshness, scope, and confidence.
6. The result is presented with the utility, affected area, last-updated time, and escalation options.
Identify the correct Hyderabad electricity service area
“Hyderabad” is not sufficient as an operational identifier. Electricity distribution responsibility can vary by service territory and address. A production agent should determine the relevant distribution company or operational region from the user’s location rather than hard-coding one provider.
Depending on the address, the agent may need to distinguish between service areas associated with Telangana’s distribution utilities, including Hyderabad-area operations and neighbouring districts. The exact provider must be verified against the current official utility information because administrative boundaries, portals, and contact channels can change.
Useful location inputs include:
- GHMC zone, circle, or ward
- Locality, colony, or neighbourhood
- Landmark and PIN code
- Electricity service or consumer number
- Latitude and longitude, only with user consent
- Feeder, substation, or transformer identifier, when available
Do not infer a utility solely from a broad city name. “Kondapur,” “LB Nagar,” or “Secunderabad” may still require a more precise address or consumer identifier. Ask a clarifying question when the location maps to multiple service areas.
Design the WebMCP tool contract
The tool contract should be narrow, explicit, and easy to validate. Avoid exposing a general-purpose browsing action if the agent only needs outage status. A constrained schema reduces accidental data access and makes testing easier.
Example request schema:
{
"name": "get_power_outage_status",
"description": "Return current or recently reported electricity outage information for a Hyderabad service location.",
"inputSchema": {
"type": "object",
"properties": {
"location_text": {
"type": "string",
"description": "Locality, landmark, address, or PIN code"
},
"latitude": {
"type": "number",
"minimum": 15.0,
"maximum": 18.0
},
"longitude": {
"type": "number",
"minimum": 77.0,
"maximum": 80.0
},
"consumer_number": {
"type": "string",
"description": "Optional utility-issued service identifier"
},
"language": {
"type": "string",
"enum": ["en", "te"]
}
},
"additionalProperties": false
}
}The implementation should enforce additional rules that JSON Schema alone may not capture:
- Require at least one location signal.
- Reject coordinates outside the expected geographic envelope.
- Never log a consumer number in plaintext unless necessary and authorised.
- Apply length limits to free-form location text.
- Normalise Unicode without destroying Telugu text.
- Require explicit consent before using precise device location.
- Prevent the same request from being used to access unrelated account data.
A separate tool can resolve service territory:
{
"name": "resolve_hyderabad_service_area",
"input": {
"location_text": "Madhapur, Hyderabad",
"pin_code": "500081"
}
}Its output should include a provider identifier, confidence score, matched geography, and a reason when clarification is needed.
Connect WebMCP to official outage data
The preferred source hierarchy is:
1. An official, documented utility API.
2. An authorised utility portal integration.
3. A government or utility-maintained open-data feed.
4. A carefully controlled fallback that reads a public status page, subject to its terms and technical permissions.
5. A user-facing helpline or complaint channel when no live status source exists.
Do not present a scraped page as an authoritative API. If a utility provides only a dynamic website, use an approved integration or browser automation with strict limits, and label the result as portal-derived. Respect robots directives, authentication requirements, rate limits, copyright, and terms of service.
A normalised internal response might look like this:
{
"status": "outage_reported",
"provider": "official_utility_identifier",
"area": "Matched locality or feeder area",
"cause": "planned_maintenance",
"started_at": "2026-09-03T10:15:00+05:30",
"estimated_restoration_at": "2026-09-03T13:00:00+05:30",
"last_updated_at": "2026-09-03T11:20:00+05:30",
"source_url": "https://official.example/status",
"confidence": "high",
"status_scope": "feeder_area"
}Use Asia/Kolkata timestamps and retain the original source timestamp. If the provider gives no restoration estimate, return null rather than inventing one. Distinguish between no_outage_found, outage_reported, planned_outage, data_unavailable, and location_unresolved.
Build the agent decision flow
The agent should not immediately call the outage tool for every question. A robust decision flow separates intent detection, location collection, data retrieval, and response generation.
1. Detect the outage intent
Recognise questions such as:
- “Is there a power cut in Gachibowli?”
- “When will electricity return in Kukatpally?”
- “Check the outage near my home.”
- “Current power status in Hyderabad.”
If the user is reporting a dangerous situation—sparking wires, fallen poles, fire, or medical risk—prioritise emergency guidance and the official emergency channel over a status lookup.
2. Resolve location
Extract locality, PIN code, landmark, coordinates, or consumer number. If the user says only “Hyderabad,” ask for a neighbourhood or service number. Do not silently use device GPS.
3. Select the authorised tool
Call the service-area resolver first when the provider is uncertain. Then invoke the outage lookup with the minimum required data. Do not call account, billing, or complaint tools unless the user explicitly requests those actions and the integration has appropriate consent controls.
4. Validate the response
Check:
- Source identity and authentication result
- Response timestamp and age
- Geographic scope
- Provider match
- Required fields and data types
- Conflicts between multiple sources
A status older than the configured freshness threshold should be labelled stale. The threshold may differ by source; a live telemetry feed and a manually updated dashboard should not be treated identically.
5. Explain uncertainty
A good answer might say: “The official status feed reports an outage affecting the feeder area serving parts of Madhapur. It was last updated at 11:20 AM IST. Your exact building is not confirmed by the feed.” This is more useful than a definitive “there is a power cut” based on a broad locality match.
Add freshness, caching, and fallback controls
Real-time outage data is often incomplete. A distribution system may know about a feeder trip before individual complaints appear, while a public portal may update only after an operator confirms the event.
Recommended controls include:
- Store
last_updated_atandretrieved_atseparately. - Set a maximum acceptable age for “live” responses.
- Cache normalised results briefly to reduce utility load.
- Use idempotency keys for repeated agent requests.
- Apply per-user and per-IP rate limits.
- Retry only transient failures, with exponential backoff.
- Never retry a complaint-submission action automatically.
- Return a clear fallback when the source is unavailable.
A fallback response should provide the official outage portal, helpline, or complaint route, plus the exact information the user should keep ready. Avoid fabricating restoration times from historical averages.
Handle Telugu, English, and Hyderabad addresses
Hyderabad location queries commonly mix English, Telugu, abbreviations, and informal landmarks. Your location layer should support Unicode and common variants without treating transliteration as a guaranteed match.
Useful normalisation steps include:
- Preserve the original user text for display and audit context.
- Generate search variants for Telugu and Latin transliteration.
- Expand common abbreviations such as “Rd,” “Nagar,” and “Colony” cautiously.
- Use PIN code and administrative geography as disambiguation signals.
- Treat landmarks as approximate, not as proof of a service address.
- Ask for a nearby main road or PIN code when confidence is low.
Do not expose a user’s full address in a public response. Show only the locality or a deliberately coarsened area unless the user has requested otherwise.
Security and privacy requirements
Power-outage tools can become an indirect path to sensitive household information. Consumer numbers, meter identifiers, precise coordinates, and account details should be protected as personal data.
Implement:
- Explicit consent for precise location access
- Encryption in transit and at rest
- Secret storage for utility credentials
- Short retention periods for location and consumer identifiers
- Redaction in logs, traces, and analytics
- Role-based access for operators
- Tool allowlists and domain restrictions
- Input validation against prompt injection and malicious URLs
- Audit records for high-impact actions
Treat all text fetched from a web page as untrusted content. A compromised page could contain instructions designed to manipulate the agent. The agent should extract only fields allowed by the adapter and should never follow instructions embedded in outage descriptions.
Testing strategy for a Hyderabad outage agent
Test the integration with both synthetic fixtures and controlled live checks. Include cases for:
- Valid locality with an active outage
- Valid locality with no reported outage
- Planned maintenance
- Ambiguous locality names
- Telugu-only and mixed-language queries
- Invalid coordinates
- Wrong provider mapping
- Stale source data
- Utility API timeout
- Rate limiting and authentication failure
- Conflicting feeds
- Emergency hazards
- Consumer-number privacy leakage
Measure more than response latency. Important metrics include location-resolution accuracy, stale-answer rate, source availability, false “no outage” responses, tool error rate, and percentage of answers containing a source timestamp.
Use a human review process for incidents where the agent gives a wrong restoration estimate, exposes account data, or directs a user to an unofficial emergency number. Maintain versioned schemas so changes to the utility adapter do not silently break the agent.
Example user experience
User: “Is there a power cut near Hitech City?”
Agent: “Which locality or PIN code should I check? Hitech City spans multiple service areas, and the official outage status is location-specific.”
User: “Madhapur, 500081.”
Agent: “The official status feed currently reports a feeder-level outage affecting parts of Madhapur. The result was last updated at 11:20 AM IST. No confirmed restoration time is available. Because the feed is not building-specific, your apartment may be on a different feeder. Would you like the official complaint or helpline option?”
This pattern is transparent: it clarifies scope, cites freshness, avoids overclaiming, and offers a next step.
Implementation checklist
Before releasing a WebMCP outage agent, verify that you have:
- An authorised utility data source
- A narrow WebMCP tool schema
- Hyderabad service-area resolution
- English and Telugu input handling
- Asia/Kolkata timestamp normalisation
- Freshness and stale-data rules
- Source and confidence fields
- Privacy controls for coordinates and consumer numbers
- Prompt-injection-resistant content extraction
- Rate limits, retries, and circuit breakers
- Official fallback channels
- Monitoring and incident review
- Tests for planned and unplanned outages
WebMCP can make outage information easier for AI agents to access, but the quality of the result depends on the underlying utility data and the safeguards around it. The strongest architecture combines official sources, explicit schemas, careful location resolution, freshness metadata, and honest communication when the system cannot confirm an exact address.
FAQ: WebMCP and Hyderabad power outages
Can WebMCP directly access live electricity data?
Only when a website or authorised integration exposes that data. WebMCP does not automatically create access to private utility systems or guarantee that a public page is real-time.
Which Hyderabad utility should the agent query?
It depends on the user’s exact service address and current distribution territory. Resolve the service area from official utility information instead of assuming that every Hyderabad query maps to one provider.
Should the agent use the user’s GPS location?
Only after explicit permission. Offer locality, PIN code, landmark, or consumer-number alternatives, and avoid retaining precise coordinates longer than necessary.
Can an agent predict when power will return?
It should display an official estimated restoration time only when one is provided and timestamped. It should not invent a prediction from historical averages.
What if no official outage API is available?
Use an authorised portal integration where permitted, clearly label portal-derived information, and provide the official helpline or complaint channel when live status cannot be verified.
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