tradingview-mcp-review

by F-e-u-e-r

Overview Schema Related Servers Score Discussions

JavaScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct action: health check, state retrieval, setting symbol/timeframe/visible range, getting OHLCV data, and screenshots. No functional overlap.
Naming Consistency3/5
Naming mixes prefixes: 'tv_' for health check, 'chart_' for state and settings, 'data_' for OHLCV, and no prefix for screenshot. While still readable, the pattern is inconsistent.
Tool Count5/5
Seven tools are well-scoped for chart review and navigation, fitting the recommended 3-15 range. Each tool serves a clear purpose without redundancy.
Completeness4/5
Core trade review workflows are covered (navigate to date, get historical OHLCV, capture screenshot). A minor gap is the absence of a tool to change chart type (e.g., candlestick to line), which could be useful but is not critical.
Average 3.7/5 across 7 of 7 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 37 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.json to 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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavioral traits. It does not state whether the change is persistent, if it triggers any side effects (e.g., resetting timeframes), or if it requires specific permissions. The agent is left guessing about the impact of this mutation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise. However, it could be slightly more informative without losing brevity (e.g., noting the chart context). It is front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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, no annotations), the description provides minimal context. It does not explain success/failure indicators, whether the chart is expected to exist, or how this interacts with sibling tools like chart_set_timeframe. The agent lacks sufficient information to use it reliably.
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% with a single well-documented parameter (symbol includes examples). The description adds no extra meaning beyond the schema, so a baseline of 3 is appropriate given the low parameter count and complete schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Change the chart symbol', which is a specific verb and resource. It distinguishes itself from siblings like chart_set_timeframe and chart_set_visible_range by focusing on the symbol aspect of chart configuration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites (e.g., a chart must be open), nor does it exclude usage in certain scenarios. The description is minimal and lacks context for the AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It fails to indicate whether this is a read or write operation, whether it affects other chart state, or if there are side effects like resetting visible range. The description adds minimal behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is efficient and front-loaded with the action, though it could be slightly more descriptive without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 param, no output schema), the description is somewhat adequate but lacks critical context such as whether the change is reversible, what the visual feedback is, or if it requires a chart to be already set (chart_set_symbol). The sibling tools suggest a trading platform context, but missing usage coordination hurts completeness.
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% and 1 parameter has enum values, so the baseline is 3. The description does not add any meaning beyond what the schema already provides, but since coverage is complete, no deduction is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Change' and the resource 'chart timeframe/resolution', which is specific enough to distinguish it from siblings like chart_set_symbol or chart_set_visible_range. It does not explicitly distinguish from data_get_ohlcv, but the resource is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 vs alternatives, such as when to change timeframe vs getting the current state. Among siblings, chart_get_state and data_get_ohlcv are related, but no exclusions or context are given.
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?
With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: 'Pages in older history as needed, so this also serves as jump-to-date.' This is valuable. However, it does not mention side effects (e.g., whether the chart range is permanently changed), error handling for invalid ranges, or any required state (e.g., chart must be loaded). The disclosure is partial but non-trivial.
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 sentences, front-loaded with the primary action, and wastes no words. The first sentence states the core functionality, and the second adds a practical use case and behavioral insight. Every sentence earns its place.
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 (2 parameters, no output schema, no annotations), the description provides sufficient context: purpose, input format, a key behavior (paging), and a use case. It does not mention prerequisites (e.g., chart must be active) or return values, but those are not critical given the tool's nature. The description is complete enough for an agent to use it 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?
Schema description coverage is 100% — both parameters already have clear descriptions in the schema (e.g., 'unix seconds'). The tool description only repeats the unit and adds a behavioral note about paging history, which does not add semantic meaning to the parameters themselves. The description does not improve upon the schema's parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's primary action: 'Zoom the chart to a specific date range (unix timestamps in seconds).' It also provides a concrete use case (reviewing a past trade). While it doesn't explicitly distinguish from sibling tools like chart_set_timeframe, the verb 'zoom' and the focus on a date range make its purpose distinct enough.
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 usage by giving an example: 'pass a window around the trade time' for reviewing trades. However, it does not provide explicit guidance on when to use this tool versus alternatives (e.g., chart_set_timeframe for setting intervals) or when not to use it. The context is implied but not formalized.
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?
With no annotations provided, the description must disclose all behavioral traits. It specifies the local address (127.0.0.1:9222) and network behavior (no external requests). However, it does not describe failure modes (e.g., connection refused) or the exact format of 'current chart state', leaving some behavioral gaps.
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 sentences with no wasted words. It front-loads the primary purpose and connection details in the first sentence, then adds constraints in the second. Every sentence serves a distinct purpose.
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, parameterless tool, the description covers the core action and constraints. However, it lacks details on the return format of 'current chart state' and does not mention error behavior, which would improve completeness given no output schema.
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 0 parameters with 100% coverage, so the schema already defines all parameters. The description adds no parameter-level meaning, but the baseline according to rules is 3. The tool has no parameters, so no further semantics are needed.
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 specific verbs ('Check') and identifies the resource ('local CDP connection to TradingView Desktop', 'current chart state'). It clearly distinguishes from siblings like chart_get_state by emphasizing the connection check aspect in the tool name and description.
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 states the tool is 'Local-only' and 'performs no external network requests', providing context for when to use it. However, it does not explicitly mention when to avoid it or suggest alternative tools like chart_get_state for just reading chart state without a health check.
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?
The description reveals important behavioral traits: it refuses a window with no loaded bars, defaults to summary=true (compact stats + last 5 bars). With no annotations provided, the description carries the full burden for behavioral disclosure. However, it does not mention authentication requirements, rate limits, or the full return format, which would be helpful for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately brief but front-loads the core action and modes. Each sentence adds distinct value: mode explanation, use-case guidance, error handling, and defaults. Subtracting one point for slightly dense structure that could be broken into clearer lists for the two modes.
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 no annotations and no output schema, the description covers the key aspects: what the tool does, its two modes, when to use each, default behavior, and a usage pitfall. It is complete enough for an agent to select and invoke correctly. However, it could mention whether the data is for the active symbol or pass a symbol parameter, and what the 'stats' in summary include.
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%, so baseline is 3. The description adds context about the modes (from+to vs omit both) and the default for summary, which maps to the parameters. However, it does not explain the meaning of 'summary' beyond contrasting 'compact stats + last 5 bars' vs 'all bars', and could clarify what 'stats' includes. The description also does not compensate for the lack of parameter enum details.
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 'Get OHLCV bar data from the chart', specifying the verb (get), resource (OHLCV bar data), and source (chart). It distinguishes two modes (from+to vs omit both) and explains when each is appropriate, helping differentiate from sibling tools like chart_set_visible_range or chart_get_state.
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 guidance on when to use each mode: 'pass from+to ... when reviewing a past trade' and 'Omit both for the newest count bars.' It also warns against using the wrong mode: 'because without it you get the newest bars regardless of where the chart is navigated.' Additionally, it advises to call chart_set_visible_range for a window with no loaded bars instead of receiving a refusal.
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?
With no annotations provided, the description must disclose behavioral traits. It does mention the fixed output directory and that no path/name input is accepted, which adds transparency. However, it does not clarify side effects (e.g., file creation, potential overwrites) or performance implications, leaving gaps given the absence of annotations.
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 concise and front-loaded, with the main action stated first. Every sentence earns its place: it covers functionality, output location, and a parameter hint. It is not overly verbose.
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 moderate complexity (2 parameters, no output schema, no annotations), the description is quite complete: it explains the output path and parameter usage. The lack of details about return format or error handling is acceptable since no output schema exists, but the description adequately covers the essential usage aspects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% coverage with descriptions for both parameters. The description adds value by explaining the 'wait_for_render' parameter's purpose in the context of chart changes, which goes beyond the schema's basic description. It also clarifies the region role implicitly through 'Capture region (default full)'.
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 what the tool does: 'Take a screenshot of the TradingView chart.' It also specifies the output behavior ('Saves to the fixed generated/screenshots/ directory... and returns the path') and distinguishes it from sibling tools by focusing solely on screenshot capture, unlike health checks or state retrieval.
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 this tool (to capture a screenshot) and includes a specific usage hint for the 'wait_for_render' parameter ('use after symbol/timeframe/range changes'). However, it does not explicitly state when NOT to use it or mention alternative tools, but the sibling list makes the purpose distinct enough.
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?
Description explicitly states it's a get (read) operation, indicating no side effects. No annotations provided, so description carries full burden. It's transparent enough, though could mention it's safe to call at any time.
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?
Single concise sentence with all key information front-loaded. No wasted words.
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?
Given zero parameters and no output schema, the description covers everything needed: what the tool does and what state it returns. Sibling tools provide additional context. Complete for its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters; schema coverage is 100% trivial. Baseline score 4 per rubric since no param info needed. Description adds nothing about params but doesn't need to.
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 uses a specific verb ('Get') and resource ('current chart state'), lists included fields (symbol, timeframe, chart type, indicators), and distinguishes from siblings like chart_set_symbol. Clear and unambiguous.
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?
Implied usage is clear: read current state. No explicit when-not or alternative mention, but sibling tool names provide strong context. Lacks explicit exclusions but adequate for a simple read tool.
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:

[![tradingview-mcp MCP server](https://glama.ai/mcp/servers/F-e-u-e-r/tradingview-mcp/badges/card.svg)](https://glama.ai/mcp/servers/F-e-u-e-r/tradingview-mcp)

Score Badge

Copy to your README.md:

[![tradingview-mcp MCP server](https://glama.ai/mcp/servers/F-e-u-e-r/tradingview-mcp/badges/score.svg)](https://glama.ai/mcp/servers/F-e-u-e-r/tradingview-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/F-e-u-e-r/tradingview-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server