tiktok-downloader-mcp
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clear, distinct purpose: extracting post info, listing user posts, downloading a single post, downloading all user media, and getting user analytics. No significant overlap between any two tools.
Naming Consistency4/5All tools follow the pattern 'tiktok_<verb>_<object>', with verbs like extract, get, download. The pattern is consistent, though 'extract' vs 'get' for similar retrieval operations is a minor inconsistency.
Tool Count5/5Five tools is well-scoped for a TikTok downloader: essential operations for data extraction, listing, downloading, and analytics are covered without bloat.
Completeness4/5The surface covers the core workflow: obtain URLs, list posts, download individual or all user media, and analyze engagement. Missing features like search or hashtag downloads are beyond the stated scope, so minor gap.
Average 3.8/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 7 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states 'without downloading files' implying a read-only operation and lists the metrics returned. However, it omits details on authentication requirements, rate limits, data recency bounds, and whether the analysis is computed on-the-fly or cached. This is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately states the verb and resource. It is 20 words with no filler, and every term ('analyze', 'engagement metrics', 'without downloading') adds value. Ideal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should explain the return structure. It mentions 'top performing posts' but does not specify whether those are full post objects, IDs, or thumbnails. It also fails to describe the format of engagement metrics (e.g., per-post breakdown vs. aggregate). A user cannot fully anticipate the tool's output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for both parameters (username and max), so the baseline is 3. The description does not add any extra meaning beyond the schema descriptions; it does not clarify how 'max' affects the analysis output or what formats are accepted for username.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the explicit verb 'Analyze' targeting 'a TikTok profile's recent engagement metrics', listing specific outputs like views, likes, comments, shares, engagement rate, and top performing posts. It clearly differentiates from sibling tools, which focus on extraction or downloading, by emphasizing 'without downloading files'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives like tiktok_get_user_posts or tiktok_extract_post. While it hints at not needing downloads, it does not explain trade-offs (e.g., aggregated vs. raw data) or scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden. It discloses that the tool returns post IDs, upload dates, and URLs, which is useful. However, it does not mention any behavioral traits like rate limits, authentication needs, or pagination behavior beyond 'max' parameter. The description is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently captures purpose and output. It is front-loaded with key information. No unnecessary words, but could be slightly more structured with examples or usage hints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's relative simplicity (2 params, no output schema, no nested objects) and sibling context, the description is sufficient for basic understanding. However, it lacks guidance on when to use this vs tiktok_get_user_analytics or tiktok_download_user_media, and does not explain what happens if the max is exceeded or if the user has no posts. A more complete description would include a note about the scope of 'recent' and any limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema; the 'max' parameter is already described with default and purpose, and 'username' is well-documented. The description reiterates that username accepts @ or plain or URL, which is helpful but not a significant addition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists recent post IDs, upload dates, and URLs for a TikTok user or profile URL. The verb 'list' and resource 'TikTok user posts' are specific, but it does not distinguish from siblings like tiktok_extract_post or tiktok_download_post, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching recent posts from a user, and mentions that the input can be a username or profile URL. However, it lacks guidance on when to use this tool versus alternatives (e.g., tiktok_download_user_media for downloading, tiktok_get_user_analytics for analytics). No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full responsibility for behavioral disclosure. It explicitly states the tool downloads content, creates a date-named folder, and saves metadata as post.json, giving the agent a clear operational model. However, it does not mention any potential rate limits, authentication requirements, or handling of unavailable posts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, informative sentence that front-loads the action and output specifics. Every element (action, media type, folder naming, metadata) is purposeful, with no superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and a simple 2-parameter tool with 100% schema coverage, the description adequately covers input and output structure. It could be enhanced by noting error behavior (e.g., what happens if the URL is invalid) or requiring authentication, but for a straightforward download tool, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add further details about the parameters beyond what the schema already provides (url and output_dir with defaults). It reiterates the output directory usage indirectly but adds no new semantic depth.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (download), resource (TikTok post), and key features (unwatermarked HD MP4 video or photo slides). It distinguishes itself from siblings by specifying the output format—a date-named folder with metadata—but it does not directly contrast with sibling tools like tiktok_extract_post or tiktok_download_user_media.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies downloading individual posts, which differs from siblings that extract data or download user media, but it does not provide explicit when-to-use guidance or exclusion criteria. The agent must infer usage context from sibling names rather than from the description itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It clearly states the output format ('organized date folders (YYYY-MM-DD_<id>)', 'post.json', 'account_summary.json') and that it handles photos and HD MP4 videos. It does not mention rate limits or authentication, but as a download tool the behavior is reasonably transparent for agent decision-making.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence that packs key information: what is downloaded (photos and videos), how it is organized (date folders), metadata files included, and account summary. It is concise and front-loaded, though additional details about the format could be considered but would add length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is fairly complete. It explains the output structure and file naming, which is critical for an agent to understand what will be created. Missing details on rate limits or required permissions, but for a download tool the core behavior is covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the output structure and overall purpose, but does not add specific parameter-level details beyond what the schema already provides. However, the enum for media_type and defaults for max and output_dir are self-explanatory. Scores 4 because the description context complements the schema well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('download') and resources ('media from a TikTok account') and clearly distinguishes from siblings like tiktok_extract_post or tiktok_get_user_posts by mentioning 'organized date folders', 'post.json', and 'account_summary.json'. It differentiates itself well.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (to download all media from a TikTok account) but provides no explicit guidance on when not to use it or alternatives. Given sibling tools like tiktok_get_user_posts or tiktok_download_post exist, it would benefit from stating when to prefer this over fetching or downloading a single post.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses that the tool extracts media (implying it is a read operation) and returns engagement metrics, but it does not mention any potential destructive side effects, authorization requirements, rate limits, or data freshness. The lack of annotations and limited behavioral detail keeps this at a mid-range score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the tool's purpose and deliverables without any wasted words. Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has only one parameter with full schema coverage, no output schema, and no nested objects, the description is complete enough for an agent to understand what the tool returns and how to invoke it. The specifics about media type (photos, video, audio) and nine engagement metrics cover the essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the single 'url' parameter thoroughly. The description adds no further syntax or formatting guidance beyond what the schema provides, leading to a baseline score of 3. No additional value is contributed for the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('extract'), the specific resource ('TikTok URL'), and lists the exact deliverables (unwatermarked HD photos, video download URL, audio, and nine categories of engagement metrics). This specificity and completeness distinguish it effectively from sibling tools like tiktok_download_post or tiktok_get_user_posts, which have different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when you need unwatermarked media and full metrics from a single TikTok post URL. However, it does not explicitly state when NOT to use this tool (e.g., if only download is needed, use tiktok_download_post) or suggest alternatives for user-level data. The context is clear but omits exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/abdouldotdev/tiktok-downloader-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server