Enables Claude to perform real-time web searches and fetch web page content via MCP, using OpenAI-compatible APIs with optional Tavily or Firecrawl engines
Detailed security scan evidence is not public for this MCP yet. Public identity, registry metadata, and independently observed protocol inventory remain available.
Installation and connection instructions are shown only when supported by retained package, repository, or endpoint evidence.
Version 0.1.1 declares 1 executable entrypoint.
npm install --save-exact openai-search-mcp@0.1.1npx -y -p openai-search-mcp@0.1.1 openai-search-mcp{
"mcpServers": {
"openai-search-mcp": {
"command": "npx",
"args": [
"-y",
"-p",
"openai-search-mcp@0.1.1",
"openai-search-mcp"
]
}
}
}| Canonical slug | openai-search-mcp-fe85baf0 | Deployment | Local Only |
|---|---|---|---|
| Canonical package | npm:openai-search-mcp | Repository | lie5860/openai-search-mcp |
| First published | — | Latest release | — |
| Last security verification | — | Classification confidence | 90% |
| Publication | Draft | Official distribution | Not verified |
| Channel | Identifier | Current version | Versions | Source |
|---|---|---|---|---|
| npm | openai-search-mcp | 0.1.1 | 1 | Repository |
| Package | Version | Published / observed | Inventory | Security scan |
|---|---|---|---|---|
| npmopenai-search-mcp | 0.1.1Current | Sep 5, 2026 | 5 toolsSucceeded · 0 resources · 0 prompts | Evidence restricted |
Independently scan the exact version your agents use, receive alerts when its risk changes, and investigate every finding with retained version evidence.
No public current-version evidence is available yet.
| Tool | Category | Annotations | Risk |
|---|---|---|---|
get_config_infoReturns the current OpenAI Search MCP server configuration information and tests the connection.
This tool is useful for:
- Verifying that environment variables are correctly configured
- Testing API connectivity by sending a request to /models endpoint
- Debugging configuration issues
- Checking the current API endpoint and settings
Returns
-------
A JSON-encoded string containing configuration details:
- `api_url`: The configured OpenAI-compatible API endpoint
- `api_key`: The API key (masked for security, showing only first and last 4 characters)
- `model`: The currently selected model for search and fetch operations
- `debug_enabled`: Whether debug mode is enabled
- `log_level`: Current logging level
- `log_dir`: Directory where logs are stored
- `config_status`: Overall configuration status (✅ complete or ❌ error)
- `connection_test`: Result of testing API connectivity to /models endpoint
- `status`: Connection status
- `message`: Status message with model count
- `response_time_ms`: API response time in milliseconds
- `available_models`: List of available model IDs (only present on successful connection)
Notes
-----
- API keys are automatically masked for security
- This tool does not require any parameters
- Useful for troubleshooting before making actual search requests
- Automatically tests API connectivity during executionInput schema{
"type": "object",
"properties": {}
} | — | — | |
switch_modelSwitches the default AI model used for search and fetch operations, and persists the setting.
This tool is useful for:
- Changing the AI model used for web search and content fetching
- Testing different models for performance or quality comparison
- Persisting model preference across sessions
Parameters
----------
model : str
The model ID to switch to (e.g., "gpt-4o", "gpt-4o-mini")
Returns
-------
A JSON-encoded string containing:
- `status`: Success or error status
- `previous_model`: The model that was being used before
- `current_model`: The newly selected model
- `message`: Status message
- `config_file`: Path where the model preference is saved
Notes
-----
- The model setting is persisted to ~/.config/openai-search/config.json
- This setting will be used for all future search and fetch operations
- You can verify available models using the get_config_info toolInput schema{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"model": {
"anyOf": [
{
"type": "string",
"enum": [
"gpt-4o",
"gpt-4o-mini",
"gpt-4-turbo"
]
},
{
"type": "string"
}
],
"description": "Model ID"
}
},
"required": [
"model"
]
} | — | — | |
toggle_builtin_toolsToggle Claude Code's built-in WebSearch and WebFetch tools on/off.
Parameters: action - "on" (block built-in), "off" (allow built-in), "status" (check)
Returns: JSON with current status and deny listInput schema{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"action": {
"default": "status",
"description": "Action type",
"type": "string",
"enum": [
"on",
"off",
"status"
]
}
}
} | — | — | |
web_fetchFetches and extracts the complete content from a specified URL and returns it as a structured Markdown document.
The `url` should be a valid HTTP/HTTPS web address pointing to the target page.
Ensure the URL is complete and accessible (not behind authentication or paywalls).
`fetch_engine` (optional): Which engine to use. When omitted, the server uses the `FETCH_ENGINE` env (default `llm`). `llm` = OpenAI-compatible model; `tavily` / `firecrawl` = dedicated crawl (set TAVILY_API_KEY or FIRECRAWL_API_KEY).
Returns
-------
A Markdown-formatted string containing:
- Metadata header (source URL, title, fetch timestamp)
- Table of Contents (if applicable)
- Complete page content with preserved structure
- All text, links, images, tables, and code blocks from the original page
Notes
-----
- Does NOT summarize or modify content - returns complete original text
- `tavily` / `firecrawl` perform real HTTP fetch and handle anti-bot; `llm` depends on the model's browse capability.Input schema{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"url": {
"type": "string",
"description": "The URL of the web page to fetch"
},
"fetch_engine": {
"description": "Engine for fetch: llm (model), tavily (Tavily API), firecrawl (Firecrawl API). When omitted, server uses FETCH_ENGINE env.",
"type": "string",
"enum": [
"llm",
"tavily",
"firecrawl"
]
}
},
"required": [
"url"
]
} | — | — | |
web_searchPerforms a third-party web search based on the given query and returns the results as a JSON string.
The `query` should be a clear, self-contained natural-language search query.
When helpful, include constraints such as topic, time range, language, or domain.
The `platform` should be the platforms which you should focus on searching, such as "Twitter", "GitHub", "Reddit", etc.
The `min_results` and `max_results` should be the minimum and maximum number of results to return.
Returns
-------
A JSON-encoded string representing a list of search results. Each result includes at least:
- `url`: the link to the result
- `title`: a short title
- `summary`: a brief description or snippet of the page content.Input schema{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query keyword"
},
"platform": {
"description": "Specify search platform",
"type": "string"
},
"min_results": {
"default": 3,
"description": "Minimum number of results",
"type": "number"
},
"max_results": {
"default": 10,
"description": "Maximum number of results",
"type": "number"
}
},
"required": [
"query"
]
} | — | — |
| Endpoint | Transport | Authentication | Health | Observed |
|---|---|---|---|---|
| No verified remote endpoint is linked. | ||||
Install the selected package version with: npm install --save-exact openai-search-mcp@0.1.1
openai-search-mcp Server exposed 5 tools during independent protocol observation, including get_config_info, switch_model, toggle_builtin_tools, web_fetch, web_search.
The selected current version does not yet have completed public verification. Unknown does not mean clean or vulnerable.
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Association is based on retained identity fields; it does not by itself prove first-party publication.
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