Click on "Deploy 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., "@hills-mcp-server Tell me about Helvellyn"
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.
An MCP server for exploring British and Irish hills: Munros, Wainwrights, Corbetts, Marilyns and more. No API key needed, works offline.
Tool | Description |
| Find hills near a lat/lon, sorted by distance, with optional classification filter |
| Search hills by name |
| Full detail for one hill: height, drop, grid reference, classifications, links |
| All hills in a classification (Munros, Wainwrights, etc), with optional height filter |
| Database overview: hills per classification and country |
Related MCP server: MCP Weather Free
No API keys needed. Just add to Claude Code:
claude mcp add hills -- npx -y @michaelhutchinson/hills-mcp-serverOr add to Claude Desktop's claude_desktop_config.json:
{
"mcpServers": {
"hills": {
"command": "npx",
"args": ["-y", "@michaelhutchinson/hills-mcp-server"]
}
}
}Restart Claude Code or Claude Desktop and you're ready.
"Which Munros are within 20km of Fort William?"
"Tell me about Helvellyn"
"List the Wainwrights"
"What's the highest hill in Wales?"
"Find hills near me over 600m" (Claude will ask for your location)
"Search for hills called Ben More"
"How many Corbetts are there?"
"Which country has the most Marilyns?"
Hill data comes from a bundled snapshot of the Database of British and Irish Hills (DoBIH) v18.5, which covers 21,576 hills across Britain and Ireland.
The data ships inside the package, so lookups run locally: answers are instant and there are no network calls at runtime. DoBIH is updated a few times a year, and the package is re-released to track it.
To rebuild the snapshot from a new DoBIH release:
curl -sL -o /tmp/hillcsv.zip https://www.hill-bagging.co.uk/dobih-downloads/hillcsv.zip
unzip -o /tmp/hillcsv.zip -d /tmp
npm run build-data -- /tmp/DoBIH_v18_5.csvMIT. The licence covers the code in this repository only.
This is an unofficial, community-built tool. It is not affiliated with or endorsed by the Database of British and Irish Hills team. Hill data © the DoBIH contributors, licensed CC-BY 4.0, from the Database of British and Irish Hills.
Find British and Irish hills near a location. Provide latitude and longitude coordinates. Returns hills sorted by distance, optionally filtered to one classification (e.g. only Munros).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to show (default 25, max 100) | |
| latitude | Yes | Latitude of the location | |
| longitude | Yes | Longitude of the location | |
| radius_km | No | Search radius in km (default 20, max 200) | |
| classification | No | Only include hills in this classification, e.g. 'Munros', 'Wainwrights' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that results are sorted by distance and optionally filtered by classification, which are key behaviors. It does not explicitly declare read-only status, but the nature of 'find' implies non-destructive behavior. It omits details like pagination or result formatting, but the schema covers limits and radius, so the description adds adequate transparency for a search tool.
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 long, front-loaded with the purpose, and every clause adds value. It efficiently covers what the tool does, the required input, and optional behavior without any redundant filler.
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?
For a geospatial search tool with five parameters and no output schema, the description is fairly complete: it explains the core output (hills sorted by distance) and the optional classification filter. It does not describe edge cases like no results or the exact return structure, but the schema covers parameter constraints, and the sibling tools provide enough context for an agent to infer typical list behavior. Some gaps remain, but overall it is solidly complete.
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 description coverage is 100%, so all parameters are already documented. The description adds a bit of context by highlighting latitude/longitude as the required inputs and mentioning the classification filter, but it does not add syntax or format details beyond the schema. This meets the baseline of 3 without significant extra semantic value.
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 finds British and Irish hills near a given location, which is a specific verb+resource. It differentiates from sibling tools like search_hills by emphasizing geospatial proximity (latitude/longitude) and distance sorting, making its niche obvious.
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 specifies that latitude/longitude are required and that classification filtering is optional, giving clear context on how to invoke the tool. However, it does not explicitly mention when to prefer this over search_hills (e.g., when you have coordinates instead of a name), and no exclusions or alternatives are named. This is clear context without explicit when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get full details for one hill by name or DoBIH number: height, drop, grid reference, coordinates, county, classifications, and links.
| Name | Required | Description | Default |
|---|---|---|---|
| hill | Yes | Hill name (best match is used) or DoBIH number, e.g. 'Helvellyn' or '2314' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. The description lists return fields and indicates a read operation, but it does not disclose potential 'best match' behavior (which appears in the schema) or behavior on not-found. It provides basic transparency but lacks edge-case behavior.
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 sentence that front-loads the purpose ('Get full details for one hill') and lists the details. It is efficient and clear, though the list of fields adds length; it still avoids wasted words.
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?
With no output schema, the description explains the return values by listing the fields returned. For a simple get-details tool with one parameter, this is sufficient context. It could mention what happens if no hill is found, but that is not critical given the simple nature.
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 already covers the single parameter 'hill' with a description including example and best-match behavior. The description repeats 'by name or DoBIH number' but adds no additional semantics beyond the schema, so the baseline for high coverage applies.
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 gets full details for a single hill, listing specific attributes (height, drop, grid reference, coordinates, county, classifications, links). This is a specific verb+resource and distinguishes it from siblings like search_hills and find_nearby_hills.
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?
It explicitly says the tool is for one hill and how to specify it (by name or DoBIH number), which gives clear context. It does not explicitly name alternatives, but the singular focus implies this is not for searching or listing, making usage fairly clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Overview of the hills database: total hills, counts per classification (Munros, Wainwrights...), and counts per country.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It explains what data is returned but does not disclose any edge cases (e.g., empty database, performance characteristics) or response format. For a read-only stats tool, this is adequate but not exceptional.
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 that efficiently conveys the purpose and contents. No wasted words.
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?
With no output schema, the description adequately explains the return content (total hills, per-classification and per-country counts). It lacks a bit of structural detail but is complete for a simple aggregation tool.
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 the baseline is 4. The description adds no parameter-specific semantics, but none are needed.
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 provides an overview of the hills database with specific aggregate metrics (total hills, per-classification counts, per-country counts). This distinguishes it from siblings like get_hill_details (individual hill) and search_hills (query). The verb 'get' is implied by the name and 'Overview' indicates retrieval.
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 use for database-wide statistics but does not explicitly mention when to use it over sibling tools. No exclusions are stated, but the context is clear enough for a no-parameter tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all hills in a classification (Munros, Wainwrights, Corbetts, Marilyns...), sorted by height, with an optional height range filter.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to show (default 25, max 100) | |
| max_metres | No | Only hills at most this high (metres) | |
| min_metres | No | Only hills at least this high (metres) | |
| classification | Yes | Classification name, e.g. 'Munros', 'Wainwrights', 'Corbetts' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full behavioral burden, but it fails to disclose the default/max limit of 25/100 from the schema. Saying 'List all hills' is misleading when the limit parameter caps results, and no pagination or output format is described. The description does mention sorting and height-range filtering, but the limit omission is a significant gap.
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 sentence with no filler, front-loaded with the action verb 'List'. It efficiently conveys the resource, examples, sorting, and filtering in one line, earning every word.
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?
For a read-only list tool with no output schema and no annotations, the description covers the core purpose, sorting, and filtering. However, it does not mention the limit parameter, which means a caller could mistakenly expect all hills rather than a capped result set. This is a notable completeness gap given the schema's limit behavior.
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 already covers all four parameters with descriptions, giving a baseline of 3. The description adds some context by grouping min_metres and max_metres as an 'optional height range filter' and providing classification examples, but it does not add syntax-level detail or mention the limit parameter.
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 'List' and identifies the resource as 'hills in a classification' with concrete examples (Munros, Wainwrights, Corbetts). It also distinguishes itself from siblings by noting sorting by height and optional height-range filtering, making it clearly different from search, nearby, details, or stats tools.
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 implied usage is clear: use this when you need a list of hills in a given classification. However, there is no explicit guidance about when to choose this over sibling tools like search_hills or find_nearby_hills, and no alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search British and Irish hills by name. Returns ranked matches with height, county, and DoBIH number.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to show (default 10, max 100) | |
| query | Yes | Hill name or part of one, e.g. 'Helvellyn', 'Scafell' |
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 discloses that results are 'ranked matches' and specifies return fields (height, county, DoBIH number). While it doesn't mention auth or rate limits, 'search' inherently implies a read-only operation, and the output behavior is sufficiently described.
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 concise sentences: the first states purpose and scope, the second summarizes output. No wasted words, no redundancy, and critical information is 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?
For a simple search tool with two well-documented parameters and no output schema, the description adequately covers what it does, result ranking, and the key fields returned. It is complete enough for an agent to select and invoke 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?
Schema description coverage is 100%: both 'limit' and 'query' have descriptions with constraints and examples. The tool description adds little beyond the schema, so the 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?
Description uses specific verb 'Search' and resource 'British and Irish hills by name', which clearly differentiates it from siblings like find_nearby_hills (by location) and get_hill_details (details). It also states the output type (ranked matches with fields), further clarifying its role.
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 clearly implies when to use the tool: when searching by hill name. It does not explicitly mention alternatives or exclusions, so it does not earn a 5, but the context is unambiguous and sibling names help disambiguate.
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.
v1.0.0find_nearby_hillsget_hill_detailsget_hill_statsget_listsearch_hillsScored across 5 tools
Each tool has a clearly distinct purpose: location-based search, name-based search, detail lookup, database stats, and classification listing. There is no overlap or ambiguity between them.
All tool names follow a consistent verb_noun pattern using snake_case (find_nearby_hills, search_hills, get_hill_details, get_hill_stats, get_list). While the verbs vary (find, search, get), the pattern is uniform and predictable.
With 5 tools, the server is tightly scoped to its purpose of querying a hills database. Each tool covers a distinct aspect of discovery and retrieval without superfluous additions.
The tool set covers the full lifecycle for a read-only reference database: discovery (find, search, list), detail viewing, and statistical overview. No obvious gaps exist for typical usage scenarios.
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