notifly-mcp-serverofficial
A
licenseNot graded
qualityC
maintenanceEnables AI agents to search Notifly documentation and SDK code examples for seamless integration.
24
1
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DarkFunnels documentation
Server Details
Search and read the DarkFunnels docs: WhatsApp AI sales agents connected by QR, no Meta Cloud API.
If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- darkfunnels-ai/darkfunnels-mcp
- GitHub Stars
- 0
Available Tools
3 toolsquery_docs_filesystem_dark_funnelsARead-onlyIdempotentInspect
Run a read-only shell-like query against a virtualized, in-memory filesystem rooted at / that contains ONLY the DarkFunnels documentation pages and OpenAPI specs. This is NOT a shell on any real machine — nothing runs on the user's computer, the server host, or any network. The filesystem is a sandbox backed by documentation chunks.
This is how you read documentation pages: there is no separate "get page" tool. To read a page, pass its .mdx path (e.g. /quickstart.mdx, /api-reference/create-customer.mdx) to head or cat. To search the docs with exact keyword or regex matches, use rg. To understand the docs structure, use tree or ls.
Workflow: Start with the search tool for broad or conceptual queries like "how to authenticate" or "rate limiting". Use this tool when you need exact keyword/regex matching, structural exploration, or to read the full content of a specific page by path.
Supported commands: rg (ripgrep), grep, find, tree, ls, cat, head, tail, stat, wc, sort, uniq, cut, sed, awk, jq, plus basic text utilities. No writes, no network, no process control. Run --help on any command for usage.
Each call is STATELESS: the working directory always resets to / and no shell variables, aliases, or history carry over between calls. If you need to operate in a subdirectory, chain commands in one call with && or pass absolute paths (e.g., cd /api-reference && ls or ls /api-reference). Do NOT assume that cd in one call affects the next call.
Examples:
tree / -L 2— see the top-level directory layoutrg -il "rate limit" /— find all files mentioning "rate limit"rg -C 3 "apiKey" /api-reference/— show matches with 3 lines of context around each hithead -80 /quickstart.mdx— read the top 80 lines of a specific pagehead -80 /quickstart.mdx /installation.mdx /guides/first-deploy.mdx— read multiple pages in one callcat /api-reference/create-customer.mdx— read a full page when you need everythingcat /openapi/spec.json | jq '.paths | keys'— list OpenAPI endpoints
Output is truncated to 30KB per call. Prefer targeted rg -C or head -N over broad cat on large files. To read only the relevant sections of a large file, use rg -C 3 "pattern" /path/file.mdx. Batch multiple file reads into a single head or cat call whenever possible.
When referencing pages in your response to the user, convert filesystem paths to URL paths by removing the .mdx extension. For example, /quickstart.mdx becomes /quickstart and /api-reference/overview.mdx becomes /api-reference/overview.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| command | Yes | A shell command to run against the virtualized documentation filesystem (e.g., `rg -il "keyword" /`, `tree / -L 2`, `head -80 /path/file.mdx`). |
TDQS
A5/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds substantial behavioral context: statelessness, output truncation to 30KB, no real machine/network/process execution, sandbox-backed filesystem, and working directory reset behavior. This goes well beyond the annotation baseline and prevents misuse.
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 long but every section earns its place: core identity, usage boundaries, workflow, statelessness caveat, examples, output limit, and URL conversion. Critical constraints are front-loaded, and the examples are grouped for readability without redundancy.
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?
The description is complete for a single-parameter tool with no output schema: it covers what commands exist, how to read pages, how to search, how to handle statelessness, output truncation, and how to map filesystem paths to URL paths. Nothing an agent needs to correctly invoke the tool is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage for the single `command` parameter is 100%, the description dramatically expands the parameter's meaning with supported command lists, command chaining with `&&`, absolute path usage, file-reading patterns, and concrete examples. It also clarifies output limits and how to invoke `--help`, which the schema alone does not convey.
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 states a specific verb ('Run'), resource ('virtualized, in-memory filesystem rooted at `/`'), and exact scope (DarkFunnels docs and OpenAPI specs). It clearly distinguishes itself from sibling search_dark_funnels by explaining that it reads pages and performs exact/regex search, while the search tool is for broad conceptual queries. The 'no separate get page tool' note removes ambiguity about how to read documentation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use this tool vs. the search tool: use search for broad/conceptual queries, and use this tool for exact keyword/regex matching, structural exploration, or reading a specific page. It also provides a workflow, command guidance, and examples that make the invocation conditions unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_dark_funnelsSearch documentationARead-onlyIdempotentInspect
Search across the DarkFunnels knowledge base to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about DarkFunnels, find specific documentation, understand how features work, or locate implementation details. The search returns contextual content with titles and direct links to the documentation pages. If you need the full content of a specific page, use the query_docs_filesystem tool to head or cat the page path (append .mdx to the path returned from search — e.g. head -200 /api-reference/create-customer.mdx).
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query | |
| language | No | Filter to specific language code (e.g., 'zh', 'es'). Defaults to 'en' |
TDQS
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive traits. The description adds valuable behavioral context: search returns contextual content with titles and links rather than full pages, and how to retrieve full content by appending .mdx. This goes beyond the annotation baseline.
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?
Three concise sentences, each with a distinct role: purpose, usage guidance, and return-value/next-step behavior. The example is illustrative and not redundant. No fluff or repeated schema content.
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 two-parameter search tool with no output schema, the description covers what it returns, how to use the results, and where to go for full content. An agent has all necessary context to call the tool correctly and handle the response.
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% and both parameters have descriptive text. The description does not add significant new information about the query or language parameters beyond what the schema already provides, so the baseline score 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 uses a specific verb ('Search across') and names the resource ('DarkFunnels knowledge base') with clear scope. It distinguishes itself from the sibling query_docs_filesystem_dark_funnels by explicitly noting that full page content is obtained elsewhere.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives explicit when-to-use conditions: answering questions about DarkFunnels, finding documentation, understanding features, or locating implementation details. It also provides a clear when-not-to-use directive, directing the agent to query_docs_filesystem for full page content, including a concrete example.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_feedbackSubmit documentation feedbackAInspect
Report a problem with this documentation site so the docs team can fix it. Use when a documentation page is incorrect, outdated, confusing, incomplete, or has a broken example. This is for feedback about the documentation content itself — not for product support requests or feedback about this tool or assistant.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | The documentation page path the feedback is about (e.g., the page you were reading, such as `/quickstart`). | |
| feedback | Yes | A clear description of the documentation issue or suggestion — what is incorrect, outdated, missing, or confusing. |
TDQS
A4.2/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the basic behavioral profile is covered. The description adds that feedback goes to the docs team and is for fixing the documentation, but does not disclose what happens after submission, such as confirmation or duplicate behavior. This is a minor gap given annotation coverage.
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 three sentences with no wasted wording. The primary action and target are front-loaded, followed by concrete usage examples and exclusions. Every sentence contributes to correct agent behavior.
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 two-parameter tool with 100% schema coverage and no output schema, the description is nearly complete. It covers purpose, when to use, and what not to use it for. The only missing element is any statement about the response or post-submission behavior, but this is not critical for selecting and invoking 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 covers 100% of the parameters with clear descriptions for both path and feedback. The tool description adds no additional parameter meaning, so the baseline score of 3 applies; the schema already carries the semantic weight.
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 opens with a specific verb and resource: 'Report a problem with this documentation site.' It clearly scopes the tool to documentation content issues and explicitly contrasts it with product support and feedback about the tool or assistant, which differentiates it from the sibling query/search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use conditions: 'Use when a documentation page is incorrect, outdated, confusing, incomplete, or has a broken example.' It also names exclusions, saying it is not for product support requests or feedback about the tool/assistant, giving an agent clear routing guidance.
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.
3 tool updates
- First observed
query_docs_filesystem_dark_funnels - First observed
search_dark_funnels - First observed
submit_feedback
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Add one secure layer between your agents and this server.
TDQS
A4.3/5.0
Disambiguation4/5
The search and filesystem query tools have overlapping search capabilities, but the descriptions clearly delineate use cases: search for broad/conceptual queries, filesystem for exact keyword matching, structural exploration, and reading full pages. Feedback is completely distinct.
Naming Consistency3/5
All tools start with imperative verbs, but the naming is inconsistent: one tool has a long, suffixed name (query_docs_filesystem_dark_funnels), another is short with the server suffix (search_dark_funnels), and the third is a plain verb_noun (submit_feedback). The pattern is readable but not uniform.
Tool Count4/5
Three tools is slightly minimal but appropriate for a documentation server: search, read/query, and feedback cover the essential needs. The count feels reasonable if somewhat lean.
Completeness5/5
The tool set fully covers the documentation domain: finding relevant pages, reading full content, exploring structure, and submitting feedback about errors. There are no obvious dead ends or missing core operations.