Integrates with EskomSePush's Gumroad API token system, allowing users to obtain and use API tokens for accessing load shedding data through tiered subscription plans.
Connects to the EskomSePush developer community on ZATech Slack, providing access to community support and collaboration channels for developers using the load shedding API.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@eskomsepush-mcp what's the current load shedding stage?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Model Context Protocol server for EskomSePush — bringing real-time South African load shedding data to Claude and any MCP-compatible AI client.
Built by a South African developer, for South Africans. Ask Claude about load shedding in plain language.
Tool | Description | Plan |
| Current national load shedding stage (Eskom + Cape Town) | Free ✅ |
| See how many API calls you have left today | Free ✅ |
| Find your area ID by suburb or city name | Paid 💳 |
| Upcoming events and full schedule for your area | Paid 💳 |
| Discover areas by GPS coordinates | Paid 💳 |
"What stage are we on right now?" → works on free plan
"How many API calls do I have left today?" → works on free plan
"Is there load shedding in Stellenbosch tonight?" → paid plan
"Show me the load shedding schedule for Sandton this week" → paid plan
"Find load shedding areas near me" (with GPS) → paid plan
Related MCP server: Energy Grid MCP Server
Node.js 18+
An EskomSePush API token from eskomsepush.gumroad.com/l/api
EskomSePush operates a tiered API. The free tier returns HTTP 410 Gone on area-lookup endpoints — those require a paid subscription. This MCP server exposes the full tool surface regardless of plan; unsupported tools will surface the 410 as a clear error to the client.
Plan | Cost | What works |
Free | $0 via Gumroad |
|
Paid | From $55/yr | All 5 tools |
npx eskomsepush-mcpgit clone https://github.com/zukhanyendiki9-code/eskomsepush-mcp.git
cd eskomsepush-mcp
npm install
npm run buildAdd to your claude_desktop_config.json:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"eskomsepush": {
"command": "npx",
"args": ["-y", "eskomsepush-mcp"],
"env": {
"ESP_API_TOKEN": "your-api-token-here"
}
}
}
}claude mcp add eskomsepush -e ESP_API_TOKEN=your-token -- npx -y eskomsepush-mcp{
"mcpServers": {
"eskomsepush": {
"command": "npx",
"args": ["-y", "eskomsepush-mcp"],
"env": {
"ESP_API_TOKEN": "your-api-token-here"
}
}
}
}npm run build # compile TypeScript
npm run dev # watch mode
npm run inspect # open MCP Inspector UI for testingTip: Pass
test: trueto any tool during development — it returns mock data and doesn't count against your daily quota.
Tool | Tested on free plan |
| ✅ |
| ✅ |
| ⚠️ Requires paid plan |
| ⚠️ Requires paid plan |
| ⚠️ Requires paid plan |
If you're on a paid plan and test any of the paid-tier tools, please open an issue or PR to confirm behaviour.
Plan | Calls/day |
Free | 50 |
Paid | Higher limits |
Use the check_allowance tool to monitor your usage. Use test: true while building.
PRs welcome. If you're South African and have ideas for making this more useful, open an issue.
Join the EskomSePush developer community on ZATech Slack in #eskomsepush.
MIT © Zukanye Ndiki
Check how many EskomSePush API calls you have remaining today. Free tier allows 50 calls per day.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the operation is a read (check) and mentions the free tier limit (50 calls per day). It does not detail side effects because none exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with key action and resource, and no wasted words. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no output schema, and simple purpose, the description provides all necessary context, including the free tier limit. No critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so baseline is 4. The description inherently says no parameters are needed, which is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks remaining API calls, using a specific verb ('Check') and resource ('allowance'). It distinguishes from siblings like get_area_schedule which deal with area data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking quota but does not explicitly state when to use or when not to use alternatives. Since no sibling tool serves this purpose, the context is clear but lacks direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the upcoming load shedding schedule and events for a specific area. Requires an area ID — use search_areas first if you don't have one.
| Name | Required | Description | Default |
|---|---|---|---|
| area_id | Yes | The area ID from search_areas (e.g. 'eskmo-7-stellenboschstellenboschwestern-cape') | |
| test | No | Use test data (does not count against your quota) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a read-only operation but does not disclose behaviors such as authentication requirements, rate limits, or error handling. The description is adequate but lacks depth for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The first sentence states the purpose, the second provides usage guidance. Highly concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description should explain return values. It mentions 'schedule and events' but lacks specifics on the structure or content of the response. Parameter documentation is sufficient, but the return format is vague.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters having descriptions. The description adds context by reiterating the prerequisite and tool to obtain area_id, but adds little beyond the schema's own descriptions. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'upcoming load shedding schedule and events for a specific area', uses a specific verb ('Get'), and distinguishes from siblings by directing users to search_areas for obtaining an area ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the prerequisite (area ID) and directs users to search_areas if they lack one, providing clear when-to-use and alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find load shedding areas near a GPS location. Useful when you know coordinates but not the area name.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude (e.g. -33.9249 for Cape Town) | |
| lon | Yes | Longitude (e.g. 18.4241 for Cape Town) | |
| test | No | Use test data (does not count against your quota) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose behavioral traits. It only describes the purpose and does not mention safety, side effects, authentication, or return behavior, leaving the agent uninformed about safe usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler words. Every part contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (3 params, no output schema), the description adequately explains the primary use case and differentiates from siblings. It does not explain return values, but that is acceptable without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all 3 parameters with descriptions (100% coverage). The description does not add new meaning beyond the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Find' and resource 'load shedding areas', with clear context 'near a GPS location'. It effectively distinguishes from sibling 'search_areas', which presumably searches by area name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states it is useful when coordinates are known but not the area name, suggesting use over 'search_areas'. However, it does not explicitly mention when not to use or list alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the current national load shedding stage for both Eskom and Cape Town. Use this to find out what stage we are on right now.
| Name | Required | Description | Default |
|---|---|---|---|
| test | No | Use test data instead of live data (does not count against your quota) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states the tool fetches current status and mentions the test parameter (which is documented in the schema). It does not disclose update frequency, caching, or quota details beyond the test parameter's note.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose, and contains no unnecessary information. Every part is useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an optional test parameter and no output schema. The description does not explain the return format (e.g., numeric stage, object with details), which is necessary for an agent to interpret the result correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage is 100% for the single parameter (test), and its description is already in the schema. The tool description adds no additional meaning to the parameter, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the current national load shedding stage for both Eskom and Cape Town. It uses a specific verb 'get' and identifies the resource, which distinguishes it from sibling tools like get_area_schedule or get_areas_nearby.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for finding the current stage, but does not explicitly mention when not to use this tool or provide alternatives. The sibling tools exist for area-specific or schedule lookups, but no guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for load shedding areas by name or suburb. Returns area IDs you can use with get_area_schedule. Always search first if you don't have an area ID.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Suburb, city, or area name to search for (e.g. 'Stellenbosch', 'Sandton', 'Ballito') | |
| test | No | Use test data (does not count against your quota) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It discloses that the tool returns area IDs (non-destructive read), and mentions the test parameter behavior. This is good, but could elaborate on error handling or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, and no unnecessary words. Every sentence provides value: the first defines what it does, the second gives usage guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and full parameter coverage, the description is complete. It explains the input format, output utility, and usage context. An agent can correctly invoke this tool without ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and both parameter descriptions are clear. The description adds no extra meaning beyond what the schema provides for parameters, but it does explain the output purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: searching for load shedding areas by name or suburb. It specifies the output (area IDs) and how it connects to another tool (get_area_schedule). This distinguishes it from siblings like get_areas_nearby or get_area_schedule.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises 'Always search first if you don't have an area ID,' which tells the agent when to use this tool. It implies that if an area ID is known, use get_area_schedule instead. This provides clear context but could be more explicit about alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0check_allowanceget_area_scheduleget_areas_nearbyget_statussearch_areasEach tool serves a distinct purpose: API allowance, area schedule, nearby areas, national status, and area search. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (check_allowance, get_area_schedule, get_areas_nearby, get_status, search_areas), using snake_case throughout.
Five tools is well-scoped for the EskomSePush API domain, covering the essential operations without feeling thin or overloaded.
The tool set covers all core functionality of the EskomSePush API: status, area lookup, schedule, nearby search, and API quota checking. No obvious gaps.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Real-time electricity price signals for AI agents. Spot prices, cheapest hours, and contract recommendations. 31 countries across Europe and Oceania. No authentication required.
Real-time electricity prices for AI agents. 40+ countries, 100+ zones. No auth required.
Access UK flood warnings, river levels, water quality, Met Office forecasts, and carbon data
Live status, API pricing and rate limits for ChatGPT, Claude, Gemini, Cursor and 42+ AI tools.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/zukhanyendiki9-code/eskomsepush-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server