Veezee provides LinkedIn, Reddit, and X data for AI agents via MCP, REST, SDK, and CLI with a free tier of 200 credits per day.
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Get ListedVeezee is a data platform designed specifically for AI agents, offering structured access to LinkedIn, Reddit, and X (formerly Twitter) data. The product addresses a critical gap in the AI agent ecosystem: while agents can browse the web, they often get blocked by social media platforms that restrict automated access. Veezee provides a unified API that agents can use to search for people, profiles, posts, and discussions across these three major social networks. The platform is built with a developer-first mindset, supporting multiple integration methods including MCP (Model Context Protocol), REST API, TypeScript SDK, and CLI. A standout feature is the ability for an AI agent to autonomously create its own free API key in a single API call, eliminating the need for human signup. This makes Veezee particularly appealing for developers building autonomous agents that need real-time social data for tasks like market research, candidate sourcing, brand monitoring, and prospect enrichment. The platform operates on a credit-based pricing model with a generous free tier of 200 credits per IP per day, which translates to roughly 6,000 credits per month. Paid plans start at $20 for 10,000 credits, with a subscription option at $99 per month for 80,000 credits. Veezee positions itself as a cost-effective alternative to expensive enterprise data vendors like Proxycurl and the official X API, which often require minimum commitments of thousands of dollars per month.
Unified MCP Server Veezee offers a single MCP server endpoint at https://mcp.veezee.io/all that provides access to all three platforms through one connection. Alternatively, developers can use platform-specific endpoints for LinkedIn, Reddit, or X individually. This MCP integration works with popular AI coding assistants like Claude Code, Cursor, Windsurf, VS Code, and others, allowing agents to call Veezee tools as if they were native functions.
LinkedIn Data Tools The platform provides five LinkedIn-specific tools: linkedin_resolve_url to identify LinkedIn URLs, linkedin_get_profile to retrieve person profiles, linkedin_search_people for people search, linkedin_get_company for company profiles, and linkedin_get_posts to fetch recent posts. Each tool has a fixed credit cost ranging from 2 to 10 credits per call.
Reddit Data Tools Reddit tools include reddit_search for searching posts, comments, subreddits, or users; reddit_get_subreddit for subreddit details; reddit_get_subreddit_posts for a subreddit's posts; reddit_get_user for user profiles; reddit_get_post for individual posts with optional discussion threads; and reddit_resolve_url for URL identification. Credit costs range from 2 to 6 credits.
X (Twitter) Data Tools X tools include x_search for tweet search, x_get_profile for user profiles, x_get_tweets for an account's tweets, x_get_tweet for individual tweets with full metrics, and x_resolve_url for URL identification. Credit costs are 2 to 6 credits per call.
Autonomous Key Minting A unique feature is the ability for an AI agent to create its own free API key via a single REST call to POST /v1/keys/mint. This eliminates the need for human registration, making Veezee truly agent-friendly. The key is free and includes 200 credits per IP per day. If an agent calls an endpoint without a key, the error response includes instructions on how to mint one, allowing the agent to recover autonomously.
Credit-Based Metering Veezee uses a simple credit system where each successful API call deducts a fixed number of credits. Failed calls are refunded automatically. Credits are consumed only for successful data returns, not per record or per row. This transparent pricing model contrasts with competitors that charge per profile or per tweet.
Getting started with Veezee is designed to be as frictionless as possible, especially for AI agents. The simplest path is for an agent to fetch a setup guide from https://veezee.io/agent-setup/prompt.md and follow the instructions. This guide tells the agent to make a single REST call to mint a free API key. The key is returned once and can be stored for future use. Once the key is obtained, the agent can immediately start making API calls to any of the available tools. For developers using MCP-compatible clients, setup involves adding the Veezee MCP server URL to the client's configuration file. For example, in Cursor, this means adding a JSON block to .cursor/mcp.json. After configuration, the agent can call Veezee tools directly. The CLI tool, installed via npx @veezee/sdk init, creates a local config file and provides subcommands for every tool. The TypeScript SDK offers a typed client with built-in retries and idempotency. Daily usage involves the agent making API calls as needed, with each response including the credit cost. The free tier provides 200 credits per IP per day, which covers roughly 20 to 100 calls depending on the tools used. If more credits are needed, developers can purchase credit packs starting at $20 for 10,000 credits, which are applied to the same API key without any reconfiguration.
Candidate Sourcing Recruiters can use Veezee to search LinkedIn for candidates matching specific criteria, retrieve their profiles, and cross-reference their activity on Reddit or X. For example, an agent could search for "senior software engineer" on LinkedIn, then check the candidate's Reddit posts for technical expertise. This multi-platform approach provides a richer picture than LinkedIn alone.
Market Research Companies launching a new product can use Veezee to monitor Reddit discussions for sentiment analysis. An agent can search for mentions of a competitor or product category, retrieve the top discussion threads, and summarize themes. The platform's Reddit search tool supports filtering by time range, making it easy to get recent data.
Brand Monitoring Marketing teams can set up agents to monitor X for mentions of their brand or product. The x_search tool can retrieve tweets containing specific keywords, and the x_get_tweet tool provides full metrics including likes, retweets, and replies. This allows for real-time brand sentiment tracking without manual monitoring.
Prospect Enrichment Sales teams can enrich lead lists by retrieving LinkedIn profiles for prospects. The linkedin_get_profile tool returns structured data including job title, company, location, and more. Combined with Reddit or X data, sales agents can personalize outreach based on a prospect's interests and activity.
Company Research Investors or analysts can use Veezee to research companies by retrieving their LinkedIn company page and recent posts. The linkedin_get_company tool provides company details, while linkedin_get_posts shows recent updates. This can be supplemented with Reddit discussions about the company for a well-rounded view.
Veezee offers a free tier that provides 200 credits per IP per day, which is roughly 6,000 credits per month. This is sufficient for light usage and evaluation. For heavier usage, credit packs start at $20 for 10,000 credits ($2.00 per 1,000 credits), with a minimum purchase of $20. A monthly subscription is available at $99 for 80,000 credits. Credits are applied to the same API key, so no reconfiguration is needed when upgrading. Compared to competitors, Veezee's pricing is significantly more accessible. The leading LinkedIn data vendor, Proxycurl, requires plans starting at $1,999 per month. The official X API charges per tweet and requires an approved developer account. Veezee's self-serve model with no minimum commitment makes it attractive for startups, indie developers, and small teams. However, the free tier's 200 credits per day may be limiting for high-volume use cases, and the per-call credit costs can add up quickly if many tools are used frequently. The platform does not offer a free trial beyond the daily credits, which may deter some users.
Veezee is a well-designed data platform that fills a genuine need in the AI agent ecosystem. Its focus on autonomous agent setup, multiple integration methods, and transparent credit-based pricing sets it apart from traditional data vendors. The ability for an agent to mint its own key and start using the API immediately is a thoughtful touch that reduces friction. The platform's tool set covers the most common social data needs across LinkedIn, Reddit, and X, and the credit costs are reasonable for most use cases. However, the platform has some limitations. The free tier's daily cap may be restrictive for continuous monitoring applications. The lack of a traditional free trial with a larger credit pool could be a barrier for users who want to thoroughly evaluate the service. Additionally, while the platform supports three major social networks, it does not cover other important sources like Facebook, Instagram, or YouTube. Overall, Veezee is best suited for developers building AI agents that need social data, particularly those who value autonomy and simplicity. For teams with high-volume needs, the paid plans are cost-effective compared to alternatives. Veezee is a promising product that addresses a specific pain point with a clean, developer-friendly approach.
For more details, check out their pricing page or browse the documentation. Developers interested in agent setup can read the agent setup guide.
