Campspot MCP
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., "@Campspot MCPShow me available campsites for July 4th weekend."
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.
Campspot MCP
First MCP server for the Campspot Online Booking API. Talk to your campground's reservations, sites, and rate plans from Claude, Cursor, or any MCP client.
Who is this for?
Campspot is the leading online booking platform for private campgrounds — nearly 2,000 parks and 200,000+ campsites listed on the Campspot Marketplace. Independent campground owners run their day-to-day business in Campspot: setting up sites, adjusting rate plans, watching availability, confirming reservations. This MCP exposes that surface to AI agents so a manager can ask "what's arriving this weekend and what sites are still open for July 4?" and get a real answer instead of a dashboard tour.
Related MCP server: mcp-recreation-gov
Install
pip install -e .Configure
Request a per-park API key from the Campspot support team (activation is a one-time access fee plus the standard partner authentication flow — see https://support.campspot.com/online-booking-api).
export CAMPSPOT_API_KEY="your-campspot-api-key"
# Optional: override if you are using a sandbox or per-park base URL
# export CAMPSPOT_BASE_URL="https://api.campspot.com"Use with Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"campspot_mcp": {
"command": "campspot_mcp",
"env": {
"CAMPSPOT_API_KEY": "your-campspot-api-key"
}
}
}
}Use with Claude Code
claude mcp add campspot_mcp -- campspot_mcp --env CAMPSPOT_API_KEY=your-keyTools
Tool | What it does |
| Verifies credentials by hitting |
| Returns metadata about the configured park (name, timezone, contact, address). |
| Paginated list of campsites at the park. Optional |
| Single campsite by id (name, type, capacity, rates). |
| Find sites available across a date range. Optional |
| List reservations filtered by arrival date range and status. |
| Single reservation by id. |
| List rate plans effective during an optional date range. |
Example session
You: "What's arriving at our park next weekend, and which sites are still open for July 4?"
Claude: *calls list_reservations(start_date="2026-07-04", end_date="2026-07-06") and search_availability(start_date="2026-07-04", end_date="2026-07-07"), summarises the results*
You: "Pull up reservation 9384."
Claude: *calls get_reservation(9384), shows the guest details*Engineering
Shared
httpx.AsyncClientwith connection pooling + transport retries (encode/httpx pattern).Typed exception hierarchy (
CampspotAuthError,CampspotNotFoundError,CampspotRateLimitError,CampspotAPIError,CampspotConnectionError) with structured fields (http_status,request_id,retry_after).Application-level retry with exponential backoff + full jitter on 429/5xx, honoring
Retry-After.isError-compliance: tools raise bare exceptions so FastMCP sets
isError=trueon the wire. AI agents can distinguish failure from data (Blackwell Systems audit, 54 MCPs / 20 bugs).JSONL audit log per tool call to stderr (or
CAMPSPOT_AUDIT_LOGfile) — fail-open, secrets redacted, strings truncated to 256 chars.py.typed marker (PEP 561). mypy --strict clean. ruff full rule set clean.
Development
pip install -e ".[dev]"
pytest # 23 tests, no live API required (respx mocks)
ruff check src tests # lint
mypy src # strict type-check
CAMPSPOT_API_KEY=... campspot_mcpLicense
MIT.
See also
Available Tools
8 toolsget_park_infoA
Get metadata about the configured park (name, timezone, contact info).
Use when: "which park am I configured for?", "what timezone are reservations in?", "show me the address on file".
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. The description implies a read-only operation by saying 'Get metadata', but does not explicitly state that the tool has no side effects or require no special permissions. For a simple retrieval tool, this is adequate but not explicit.
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 extremely concise, consisting of two sentences. The first sentence states the core purpose, and the second provides usage examples. Every sentence adds value, and there is no extraneous information.
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 tool's simplicity (zero parameters, clear output), the description is fully complete. The output schema exists, so the description does not need to detail return values. The sibling tools are all distinct, providing sufficient context for the agent to select this tool 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 tool has zero parameters and schema coverage is 100%. Per guidelines, 0 parameters yields a baseline of 4. The description does not need to add parameter semantics, and it correctly focuses on the output.
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 metadata (name, timezone, contact info) about the configured park. The verb 'Get' and resource 'metadata about the configured park' are specific and distinct from siblings which deal with reservations, sites, etc.
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 provides explicit example queries ('which park am I configured for?', 'what timezone are reservations in?', 'show me the address on file') that clearly indicate when to use the tool. It does not explicitly state when not to use it or list alternatives, but the examples and sibling context make usage unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_reservationA
Get a single reservation by id.
Use when: "pull up reservation 9384", "what's the balance on booking 1102?", "show me the guest details for reservation 445".
| Name | Required | Description | Default |
|---|---|---|---|
| reservation_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It merely says 'by id' with no additional behavioral details (e.g., what happens if not found, authentication needs, rate limits). Output schema provides return structure but description adds little.
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?
Very concise: two sentences plus examples. Front-loaded with action. Could include slightly more behavioral detail without harming conciseness.
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?
Output schema exists, so return values are covered. However, missing details on not-found behavior or prerequisites. For a simple lookup tool, it's adequate but not thorough.
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 has one parameter (reservation_id) with 0% description coverage. The description only says 'by id' without clarifying what the id represents (e.g., internal ID or confirmation number). Minimal added value beyond schema.
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 clearly states 'Get a single reservation by id', which is a specific verb-resource pair. It distinguishes from sibling tools like list_reservations (list multiple) and others.
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?
Provides explicit 'Use when:' with example queries, giving clear context for when to invoke. Does not explicitly list alternatives, but context makes it clear this is for single lookup.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_siteA
Get details for a single campsite by id.
Use when: "tell me about site 42", "what's the max occupancy of site 17?". Returns the full site record (name, type, capacity, rates).
| Name | Required | Description | Default |
|---|---|---|---|
| site_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states 'Returns the full site record (name, type, capacity, rates)' which adds value beyond the schema. However, it lacks details on side effects, permissions, or error conditions.
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 concise: three sentences covering purpose, usage examples, and return details. No redundant information, and key 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?
Given the tool's simplicity and the presence of an output schema, the description adequately covers the core use case and return fields. It could mention error handling or authentication, but is otherwise complete for a single-resource retrieval 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 single parameter `site_id` has no description in the schema (0% coverage). The description merely says 'by id' without clarifying expected format, range, or special values. This does not compensate for the missing schema documentation.
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 'Get details for a single campsite by id' which is a specific verb+resource. Example queries reinforce the purpose. It effectively distinguishes from sibling list or search 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 'Use when' section provides concrete example queries, demonstrating clear usage context. However, it does not explicitly mention when not to use or name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_checkA
Verify credentials work. If this fails, all other tools will too.
Use when: starting a session, debugging auth, or after rotating
CAMPSPOT_API_KEY. Calls GET /park as a lightweight endpoint that
exercises the full auth + transport stack.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses key behavioral traits: it calls a lightweight endpoint (GET /park) that exercises the full auth and transport stack, and implies that failure indicates invalid credentials. This goes beyond a simple description and helps the agent understand the tool's 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 extremely concise: two sentences plus a usage line. It front-loads the core purpose and follows with rationale and use cases. No extraneous words or repetition. Every sentence adds value.
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 tool's simplicity (zero parameters, clear purpose, and presence of an output schema), the description is fully complete. It covers what the tool does, when to use it, and what underlying resource it accesses. The agent has all necessary information to invoke it 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 tool has zero parameters, and the input schema is empty. The description adds no parameter details, which is appropriate since none exist. Baseline for zero parameters is 4, and the description confirms the lack of parameters without misleading the agent.
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?
Explicitly states the tool's purpose: 'Verify credentials work.' It uses a specific verb+resource combination and clearly distinguishes itself from sibling tools (e.g., get_park_info, list_reservations) by focusing on authentication and connectivity rather than data 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?
Provides explicit use cases: 'Use when: starting a session, debugging auth, or after rotating CAMPSPOT_API_KEY.' While it doesn't explicitly state when not to use or name alternatives, the guidance is clear and context-specific, making it easy for the agent to decide when to invoke this tool over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_ratesA
List rate plans at the park, optionally filtered by effective date.
Use when: "what rate plans are active in July?", "show me all winter rates", "is the weekend plan still configured?".
Args: start_date: ISO date YYYY-MM-DD — only include rate plans effective on or after this date. end_date: ISO date YYYY-MM-DD — only include rate plans effective on or before this date.
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | No | ||
| start_date | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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 the filtering behavior and that it lists rate plans, which is a simple read operation. Does not mention authentication, rate limits, or side effects, but the tool is inherently straightforward.
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 concise: one sentence for the main action, then 'Use when' examples, followed by structured parameter definitions. No superfluous content.
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 with two optional date filters and an output schema, the description fully covers the tool's purpose, usage, and parameters. The output schema handles return values, so no further detail is needed.
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 0%, so the description must compensate. The 'Args' section explains that start_date filters for effective on or after, and end_date for on or before, adding semantic meaning beyond the schema's type-only definitions.
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 states a specific verb ('List') and resource ('rate plans'), with optional filtering by effective date. It clearly distinguishes from sibling tools like list_reservations and list_sites.
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?
Provides explicit 'Use when:' examples (e.g., 'what rate plans are active in July?') that guide the agent. Lacks when-not-to-use or alternatives among siblings, but the examples are sufficient for common cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_reservationsA
List reservations, optionally filtered by arrival date and status.
Use when: "what's arriving this weekend?", "show me pending reservations", "count cancellations last month".
Args: start_date: ISO date YYYY-MM-DD — only include reservations whose arrival is on or after this date. end_date: ISO date YYYY-MM-DD — only include reservations whose arrival is on or before this date. status: one of "confirmed", "pending", "cancelled", or other upstream-defined value. Omit for all statuses. limit: page size (server default applies if omitted). offset: zero-based offset for pagination.
Example: start_date="2026-07-01", end_date="2026-07-31", status="confirmed", limit=25.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| offset | No | ||
| status | No | ||
| end_date | No | ||
| start_date | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavior. It states the tool lists and filters reservations but does not discuss pagination details (e.g., server default limit), ordering, or any side effects. Adequate but not comprehensive.
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?
Front-loaded with purpose, followed by usage examples, a structured Args section with clear parameter descriptions, and an example. No wasted sentences; each adds value.
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 5 optional parameters and an output schema, the description covers what the tool does and how to use filters. Could mention default ordering or server pagination limits, but overall sufficient for agent decision-making.
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 0%, but the description compensates fully by explaining each parameter's format, semantics, and valid values (e.g., ISO dates, status options, pagination offset). Includes a concrete example.
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 'List reservations, optionally filtered by arrival date and status.' It uses a specific verb (list) and resource (reservations) and distinguishes from sibling tools like get_reservation and search_availability.
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?
Provides explicit use-case examples ('what's arriving this weekend?', 'show me pending reservations') and explains each parameter with semantics and defaults, guiding when to use filters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_sitesA
List campsites at the configured park.
Use when: "what sites do I have?", "show me the first 20 sites",
"what's the offset for the next page?". Returns the API's native page
shape — dict with items (site records) and pagination metadata.
Example: limit=50, offset=0 — first page of 50 sites.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| offset | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present, so description carries burden. Discloses pagination behavior (native page shape with items and metadata) but does not mention read-only, auth needs, or side effects. Adequate for a list operation.
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?
Four sentences, front-loaded with purpose, then usage, return shape, example. No redundant info.
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 output schema exists, description covers return shape and pagination. Example completes the picture for a 2-param 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?
Input schema has 0% description coverage, but description adds example (limit=50, offset=0) and explains pagination, providing meaning beyond the schema.
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 'List campsites at the configured park' with a specific verb and resource. It distinguishes from siblings like get_site and search_availability.
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?
Provides explicit use cases with example queries ('what sites do I have?') and explains return shape. Lacks explicit when-not-to-use but gives clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_availabilityA
Find campsites available across a date range.
Use when: "is there anything open July 4-7?", "what's free next weekend?", "which of these sites is available Aug 1-5?".
Args: start_date: ISO date YYYY-MM-DD (inclusive) end_date: ISO date YYYY-MM-DD (exclusive — night of end_date does not require availability) site_ids: optional comma-separated list of site ids to scope the search. Omit to search the whole park.
Example: start_date="2026-07-04", end_date="2026-07-07".
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | Yes | ||
| site_ids | No | ||
| start_date | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses important behavioral details: start_date inclusive, end_date exclusive (night not required), and optional site_ids. Without annotations, this covers key traits. Return format is likely covered by output schema.
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?
Very concise: a clear one-line purpose, usage examples, and a structured args list. Every sentence adds value with no waste.
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?
Covers the core behavior for a search tool with 3 parameters. Output schema exists, so return values are documented elsewhere. Could mention pagination or result size, but not essential given the tool's simplicity.
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?
Adds significant meaning beyond the bare schema (which has 0% description coverage). Explains ISO date format, inclusivity/exclusivity, and the purpose of site_ids with an example of omission.
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 campsites available across a date range, with a specific verb and resource. It distinguishes from sibling tools like list_sites (which lists sites) or get_reservation (specific reservation).
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?
Provides example natural language queries (e.g., 'is there anything open July 4-7?') and explains optional site_ids scoping. However, it does not explicitly mention when to use this over alternatives like list_sites or list_reservations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
8 tool updates
v0.1.0- First observed
get_park_info - First observed
get_reservation - First observed
get_site - First observed
health_check - First observed
list_rates - First observed
list_reservations - First observed
list_sites - First observed
search_availability
TDQS
Each tool targets a distinct resource and action: park info, individual reservation, individual site, health check, rate plans, list reservations, list sites, and availability search. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (e.g., get_park_info, list_reservations, search_availability) using lowercase with underscores. No mixed conventions or vague verbs.
8 tools is well-scoped for a campsite management server. It covers essential operations without being overly numerous or sparse.
The tool set covers core read operations and availability search. Missing write operations (e.g., create reservation) but this is likely intentional for a query-focused server.
Maintenance
Resources
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