fdl-mcp-server

Name: fdl-mcp-server
Author: Nareshdevelop

by Nareshdevelop

Overview Schema Related Servers Score Discussions

JavaScript

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fdl-mcp-server

Model Context Protocol server for fivedaylaunch.com — lets Claude (and any MCP-compatible AI client) audit, compare, and redesign any small business website. Free, public, no API key required.

License: MIT MCP

What this does

Five tools that any MCP client can invoke:

Tool	What it does
`audit_website`	Deterministic 5-pillar audit (Performance, SEO, Mobile, Security, AEO) → score 0-100 + specific findings
`compare_websites`	Side-by-side scorecard of two sites with a winner
`ai_visibility_check`	How 5 major AI engines describe any business + how to improve
`get_city_dashboard`	Local economy dashboard for any US city's small business web quality
`generate_redesign_preview`	Trigger a free personalized site preview emailed to a user

All free. All call fivedaylaunch.com's public API. Zero LLM tokens consumed.

Related MCP server: foglift-mcp

Install (Claude Desktop)

Open Claude Desktop → Settings → Developer → "Edit Config" → opens claude_desktop_config.json
Add:

{
  "mcpServers": {
    "fivedaylaunch": {
      "command": "npx",
      "args": ["-y", "github:Nareshdevelop/fdl-mcp-server"]
    }
  }
}

Restart Claude Desktop.
Look for the 🔌 icon in your chat — fivedaylaunch tools should be listed.

Example prompts

After installing, ask Claude things like:

"Use fivedaylaunch to audit stripe.com"
"Compare nytimes.com and washingtonpost.com using fivedaylaunch"
"Run an AI visibility check on Tesla using fivedaylaunch"
"Show me the fivedaylaunch dashboard for Austin, Texas"
"Use fivedaylaunch to generate a redesign preview of mybusiness.com — email it to me@example.com"

Manual install (without Claude Desktop)

npx -y github:Nareshdevelop/fdl-mcp-server

The server runs on stdio. Wire it into any MCP-compatible host (Cursor, Zed, Cline, Continue, etc.).

What the API returns

Everything is JSON. Public + free.

# Free public API endpoint — try it yourself:
curl https://fivedaylaunch.com/api/audit?url=stripe.com

# Returns:
{
  "domain": "stripe.com",
  "score": 85,
  "grade": "B",
  "breakdown": { ... },
  "findings": [...]
}

Why does this exist

We built fivedaylaunch.com as a free public registry of small business website quality. The audit logic is open source (fdl-site-audit). This MCP server is the canonical way to access it from inside AI assistants.

We monetize by offering full site rebuilds at $799 flat, 5 days — the audit tool is and stays free forever.

License

fivedaylaunch.com — the main product (AI-built websites in 5 days, $799)
fdl-site-audit — the deterministic audit core, open source
fivedaylaunch.com/sites — public audit registry
fivedaylaunch.com/ai — AI visibility audit registry

Available Tools

5 tools

ai_visibility_checkA

Check how the 5 major AI search engines (ChatGPT, Perplexity, Gemini, Claude, Bing Copilot) describe a business. Returns visibility score 0-100 + specific fixes. Deterministic, no LLM tokens used.

ParametersJSON Schema

Name	Required	Description	Default
`business_name`	Yes	Business name (e.g. "Joe's Pizza Frisco")

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must carry the burden. It adds valuable behavioral traits: 'Deterministic, no LLM tokens used' and specifies the output (score 0-100 + fixes). It doesn't mention side effects, permissions, or rate limits, but the 'Check' verb implies a read-only, safe operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no redundancy. The first sentence delivers the core purpose; the second adds output details and a key attribute. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one simple parameter and no output schema, the description is sufficiently complete: it names the AI engines, the output format (score + fixes), and a critical behavioral note (deterministic, no LLM tokens). No significant gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single parameter (business_name with example). Description adds no extra parameter semantics, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'Check' and specific resource: how 5 major AI search engines (named explicitly) describe a business. This is highly specific and distinguishes the tool from siblings like audit_website or compare_websites.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies use cases: checking AI search engine visibility for a business. It does not explicitly mention when not to use it or name alternatives, but the scope is narrow and evident from context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

audit_websiteA

Run a deterministic 5-pillar audit on any website (Performance, SEO, Mobile, Security, AEO). Returns a 0-100 score with specific findings. Free, no API key, instant.

ParametersJSON Schema

Name	Required	Description	Default
`url`	Yes	Website URL or domain (e.g. "acmeplumbing.com" or "https://acme.com")

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden of disclosing behavior. It mentions 'deterministic' and 'instant', which are useful, but it doesn't explicitly state whether the tool is read-only or if it stores data. For an audit tool, the lack of side-effect disclosure is a minor gap; a 3 reflects partial disclosure without contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence that front-loads the primary action and lists key details (pillars, scoring, cost, speed). Every clause adds value without waste, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one param, no output schema), the description captures the essential return value ('0-100 score with specific findings') and key constraints. It doesn't explain the pillar scoring methodology or provide an example, but the core context is sufficient for an agent to select and use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter (url) has a schema description covering 100% of its semantics. The tool description adds 'any website' context but doesn't enhance the parameter's meaning beyond the schema. This aligns with the baseline 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Run a deterministic 5-pillar audit on any website' with a specific verb and resource. It also lists the pillars (Performance, SEO, Mobile, Security, AEO) and the return value (0-100 score). This distinguishes it from siblings like 'compare_websites' or 'ai_visibility_check' by focusing on a single-site audit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool ('on any website') and highlights its accessibility ('Free, no API key, instant'). While it doesn't explicitly contrast with sibling tools, the scope ('any website' vs. compare/dashboard) is implied. No exclusions or alternatives are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

compare_websitesA

Compare two websites side-by-side. Returns scores, grades, and a winner.

ParametersJSON Schema

Name	Required	Description	Default
`url_a`	Yes	First website to compare
`url_b`	Yes	Second website to compare

TDQS

A3.8/5.0

Behavior2/5

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 the tool returns scores, grades, and a winner, but it does not mention whether the operation is read-only, any side effects, requirements for valid URLs, or possible network dependencies. This lack of safety and side-effect disclosure is a significant gap for a tool that presumably accesses websites.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that directly states the purpose and output. There is no unnecessary fluff, and it earns its place by conveying both the action and the return type.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with only two self-descriptive parameters and no output schema, the description conveys the essential behavior: it compares two websites and returns scores, grades, and a winner. It lacks some detail about interpretation of the results, but the overall context is sufficient for an agent to decide and invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage for both parameters, each described as 'First website to compare' and 'Second website to compare'. The tool description does not add any additional meaning beyond these descriptions, so the baseline of 3 is appropriate per the schema coverage rule.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action with a specific verb 'Compare' and a specific resource 'two websites', and it mentions the output of scores, grades, and a winner. This distinguishes it from sibling tools like audit_website or ai_visibility_check, which focus on a single website or visibility check.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear context for when to use this tool: when you need to compare two websites side-by-side. However, it does not explicitly mention alternatives or when not to use it, such as when a single-site audit is needed instead. This is clear but not fully explicit about exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

generate_redesign_previewA

Request a free AI-generated redesign preview of any website. Returns a confirmation; the actual preview is emailed within 10 minutes. Costs $0.

ParametersJSON Schema

Name	Required	Description	Default
`url`	Yes	Website URL to redesign
`email`	Yes	Email to receive the preview link

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It discloses that it returns a confirmation, the preview is emailed within 10 minutes, and it costs $0, which are key behavioral traits for an async request tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the action and resource, and no unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with no annotations and no output schema, the description adequately covers the request, delivery, and cost. The only minor gap is lack of error handling or rate limit info, but that's not essential for such a simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds no extra parameter semantics beyond what the schema already provides, but it doesn't need to given the simple url/email pair.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Request') and resource ('AI-generated redesign preview') and clearly distinguishes this tool from siblings like audit_website and compare_websites.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly indicates its use case: requesting a free redesign preview. However, it doesn't explicitly mention when not to use it or compare with alternatives, so it gets a 4 rather than a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_city_dashboardA

Get the small business web-quality dashboard for a US city. Returns audited site count, mean score, top/bottom performers, and niche breakdown.

ParametersJSON Schema

Name	Required	Description	Default
`city`	Yes	US city name (e.g. "Frisco", "Dallas", "Austin")

TDQS

A3.6/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry behavioral transparency. It discloses what data is returned (audited site count, scores, etc.) but not any behavioral traits such as data freshness, computation method, or potential limitations. No mention of side effects, permissions, or error handling, leaving the tool's behavior underexplained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences, front-loading the purpose and then listing key return values. There is no redundant or unnecessary wording, making it highly efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no output schema), the description covers the essential details: what the dashboard is for, its scope, and what it returns. The lack of output schema is compensated by the explicit return breakdown. Minor gaps exist around error handling or exact city matching, but these are not critical for a simple dashboard getter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides full coverage for the single parameter 'city' with an example and description. The tool description adds no additional parameter semantics beyond what the schema already states, 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.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves a city-level dashboard, with specific verb 'get' and resource 'small business web-quality dashboard'. It also lists the exact return contents (site count, mean score, top/bottom performers, niche breakdown), distinguishing it from siblings that focus on individual audits, comparisons, or redesigns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for city-level analysis, not for auditing a specific website. It provides clear context ('for a US city') but does not explicitly mention alternatives or when to use other tools like audit_website or compare_websites. No exclusionary language is present.

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.

5 tool updatesv1.0.0Aug 7, 2026
- First observedai_visibility_check
- First observedaudit_website
- First observedcompare_websites
- First observedgenerate_redesign_preview
- First observedget_city_dashboard

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4/5.0

Disambiguation5/5

Each tool serves a clearly distinct purpose: auditing a single site, comparing two sites, checking AI visibility, viewing city stats, and generating redesign previews. There is no overlap or ambiguity between them, making it easy for an agent to select the right tool.

Naming Consistency4/5

Four of five tools follow a consistent verb_noun pattern (audit_website, compare_websites, get_city_dashboard, generate_redesign_preview). 'ai_visibility_check' deviates from the verb-first convention, making it slightly inconsistent but still readable and predictable.

Tool Count5/5

With exactly 5 tools, the set is well-scoped for a website audit/analysis service. Each tool earns its place without redundancy or bloat, and the count is within the ideal 3-15 range.

Completeness4/5

The tool surface covers the core lifecycle of website analysis: auditing, comparing, AI visibility, city-level aggregation, and redesign previews. Minor gaps exist (e.g., no tool to fetch historical audits or manage saved reports), but the core workflows are well covered.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

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