2pr is a LinkedIn exclusive AI Agent that covers the complete workflow of personal brand building through creative discovery, AI imitation writing, comment interaction, scheduled publishing and data analysis. Supports MCP protocol and can be linked with external AI such as Claude.

2pr

Core parameters and statistics

Projects	Information
Tool name	2pr (2pr.io)
Core entrance	Web App (https://2pr.io/app)
Delivery form	SaaS online service + MCP protocol interface
Price starting point	$24/month (annual payment)/$49/month (monthly payment)
Free trial	7 days (annual payment/multi-account plan) / 3 days (monthly payment individual plan)
User scale	7000+ registered users
Core carrier	LinkedIn (official API, no password, no cookies)
MCP support	Supported, can be paired with external AI Agents such as Claude
Version visibility	v2.0 (~2025-05 release)

2pr is not a general writing tool, but a vertical AI Agent deeply bound to LinkedIn scenarios. Its parameters are not complicated. Its real competitiveness lies in its "special adaptation to the LinkedIn algorithm and community tone" - such as automatically tracking hot topics across the entire platform, training writing style based on the pattern library of 2 million popular posts, and risk-free publishing through the official API.

User and market recognition

2pr is currently featured on Product Hunt and BetaList, and was mentioned by Inc. Magazine in a report on LinkedIn’s AI content ecosystem. User cases announced by the platform include:

• Kevin Meyer (Enterprise Sales + Creator, 60,000 Followers): Achieved an average of 12 million annual impressions through 2pr, maintaining a steady output while working a full-time sales job.
• Oliver Baker (Mathematician + Founder): Increased average impressions from 960 to 15,588 (16x) across 25 posts, 9x increase in engagement rate, all while maintaining a consistent personal style.
• Alexandre Mihaila (Online Pharmacy Practitioner): Impressions per post increased from 88 to 7,203 (80x).

Feedback from users on third-party evaluation platforms such as Senja focuses on dimensions such as "smooth creation experience", "imitation effect beyond the general LLM", and "will not trigger LinkedIn account ban". Some users clearly stated that 2pr works better in LinkedIn content scenarios than directly using general models such as ChatGPT/Claude.

Cost advantage

2pr’s cost structure has significant differences for C-end users, content agencies and technology developers:

• C side (individual creator): $24/month (annual payment) covers the full link of creative discovery, AI imitation writing, multi-version drafts, scheduled release, comment interaction and data analysis. By comparison, industry averages for hiring human writers range from $2,000–$5,000 per month. Even compared to a universal LLM subscription (ChatGPT Plus $20/month), 2pr saves the adaptation time from "general capabilities" to "LinkedIn specializations".
• Organization/agent operation (Multi-profile): $17/month/account (annual payment, minimum 3 accounts), each account has independent style and independent schedule, and team collaboration is not limited to the number of members. The writing cost for each customer account of a traditional agency is usually $500–$2,000/month.
• API/Developer: Link with external AI through MCP protocol, no additional API billing, included in subscription. Subscribers can embed 2pr’s capabilities into their own AI workflows (such as calling 2pr’s MCP tools for content generation through Claude).

Deduction comparison: New media operations go from ChatGPT manual writing to 2pr semi-automatic output. The time from conception to publication of a single post can be reduced from 45–60 minutes to 10–15 minutes. But this is process compression brought about by functional integration. 2pr itself does not provide API usage pricing, and enterprise-level solutions require email communication.

Main functions

• Ideas: Track real-time trending topics across LinkedIn, X (Twitter), Reddit, Substack, Hacker News and GitHub, integrated into one information stream. It has a built-in library of 2 million+ popular LinkedIn posts and supports filtering patterns by industry, format, and interaction volume.
• AI interview content generation: It is not simply "write a post for me", but guides users to express their original thoughts through preset questions, and then generates a draft consistent with their daily posting style based on the user's corpus. Each output provides 3 versions (v.0/v.1/v.2) for comparison.
• Imitation comment interaction (Engage): Automatically capture the conversation context of the post comment area, generate 3 reply options in the user's own tone, and support one-click publishing. All interactions go through the official LinkedIn API, no passwords or cookies are required.
• Schedule & Visuals: Supports schedule publishing in multiple formats such as text posts, carousel images, and image posts. AI can automatically generate custom graphics and carousel slideshows based on post content.
• Analytics and AI Coaching (Analytics): Track fan growth, single post performance, and optimal publishing time window. The built-in AI Coach module automatically generates suggestions for the writing direction of the next article based on performance data, forming a "publish → analyze → optimize → publish" concept.

Expert View: These five functions are not isolated from each other - creative discovery provides materials for writing, AI interview writing ensures consistent content style, comment interaction amplifies the social diffusion of a single post, scheduling ensures continuous output frequency, and analysis guides the next round of topic selection. It is a typical "content flywheel" architecture rather than a simple stack of functions.

Model and version evolution

The version context of 2pr is mainly based on functional milestones and does not use the large version number system of traditional software:

• ~2025-01: v1.0 initial version. Focus on LinkedIn content creative discovery and AI-assisted writing, and launch basic scheduling and comment interaction functions.
• ~2025-05: v2.0 major update. Introducing AI interview content generation (no longer "command-style" writing, changed to "question guidance + style learning"), three versions of draft comparison LinkedIn Carousel generator MCP protocol support, improved analysis panel and team collaboration functions.
• 2026-07 (current): In continuous online iteration, the official v3.0 timeline has not been disclosed. In actual use, it is recommended to pay attention to two signals: the stability of the MCP interface (critical for developer workflow integration) and the accuracy of the analysis panel data in multi-account scenarios.

Technical advantages

The technical value of 2pr can be understood from three levels:

1. LinkedIn official API integration: 2pr uses LinkedIn official API throughout the entire process, does not read cookies, does not simulate browser behavior, and does not require user passwords. This means that the user's account will not trigger LinkedIn's risk control mechanism due to "third-party tool automation" - this is its most essential difference from most browser extension LinkedIn tools.
2. Voice Cloning: Instead of simply putting the prompt word template on the user's name, the user's original expression (voice or text) is collected through the "AI interview" process, and then a draft with a consistent style is generated based on these corpus. Three versions are output at each time, covering different intonation ranges from formal to casual, allowing users to choose the version that is closest to their daily style.
3. MCP protocol support: 2pr exposes the MCP (Model Context Protocol) interface to the outside world, allowing Claude or other AI Agents that support MCP to directly call 2pr’s publishing and analysis capabilities. This means it can be embedded into larger AI workflows—for example, Claude’s Agent orchestrates collaborative tasks across multiple tools, and 2pr is responsible for content output and effect feedback on the LinkedIn side.

Mechanism→Effect→Scenario Causal Chain: The official API integration eliminates the risk of account suspension (this is the core anxiety of LinkedIn tool users), the imitation sound engine lowers the perception threshold of "AI content does not look like it is written by real people", and the MCP protocol allows technical users to integrate 2pr as a LinkedIn module into their own automated pipelines.

How to use

Use 2pr's fully qualified path:

1. Registration and Connection: Visit https://2pr.io/app, register with your email address and authorize the connection to the account through LinkedIn OAuth (the password will not be read).
2. AI Interview Setting Style: Complete the AI ​​Interview Steps when using it for the first time - answer a few questions about your industry, target audience, and writing preferences, and the system will generate an initial style model.
3. Creative Discovery → Topic Selection: Check the cross-platform hot topics and popular post library in the Ideas module, and select or combine your own topic selection direction.
4. Generate Draft: Select a topic in the Drafts module, and AI will generate 3 versions of post drafts. Tweaks can be edited manually, or regenerated.
5. Visualization and Scheduling: You can generate pictures or carousels for posts, and automatically publish them after setting the publishing time. Supports queue management and can schedule multiple articles at one time.
6. Interaction and Tracking: After publishing, you can view comments in the Engage module, and AI will automatically generate reply options. Track impressions, interactions, and follower changes in the Analytics dashboard.

MCP integration method (for developers): Configure 2pr as MCP Server in an AI client that supports MCP (such as Claude Desktop). The configuration fields are subject to official documents.

{
  "mcpServers": {
    "2pr": {
      "command": "npx",
      "args": ["@2pr/mcp-server"],
      "env": {
        "API_KEY": "<YOUR_2PR_API_KEY>"
      }
    }
  }
}

Tool behaviors that can be called after startup include create_post, schedule_post, get_analytics, list_ideas, generate_reply, etc. The specific list is subject to the official MCP document.

Product Pricing

Plan	Annual payment price	Monthly payment price	Applicable scenarios
Just for you (individual)	$24/month	$49/month	Single creator, entrepreneur
Multi-profile (multiple accounts)	$17/month/account (at least 3)	$24/month/account	Agent operating agency, team account management

All plans include a 7-day free trial (3 days for monthly paid personal plans). There is no deduction during the trial period, and it will automatically convert to a paid subscription after expiration, which can be canceled at any time. The "independent style of each account" and "unlimited number of members" of the Multi-profile plan are its key points of difference compared with competing products.

Enterprise plan: Not officially listed separately, multi-account scenarios can be covered by the Multi-profile plan. If you need customized data auditing, exclusive SLA or privatized deployment, please contact [email protected] via email.

Application scenarios

• Entrepreneur/Founder Personal Branding: Entrepreneurs share industry perspectives on LinkedIn to attract investors and customers. 2pr's AI interview function lowers the threshold for "don't know what to write", and the scheduling function ensures the discipline of continuous output. In the actual test case, Kevin Meyer maintained an average monthly exposure of one million levels while working full-time.
• Multi-customer management for operating agencies: When operating multiple customer accounts, each account requires an independent style and scheduling rhythm. 2pr's Multi-profile solution supports independent imitation models, independent scheduling, and team collaboration with no limit on the number of people. The workload that traditional agent operations require 2-3 people to maintain can be reduced to one person managing 5-10 accounts.
• B2B Marketing Team Lead Nurturing: Marketing teams use LinkedIn as a source of B2B leads by building trust by consistently publishing in-depth industry content. 2pr’s TOFU/MOFU/BOFU analysis layering (awareness → interaction → conversion) allows the team to track performance at each stage of the content marketing funnel.

Applicable people

• LinkedIn Personal Brand Creator: High-frequency output is required but time is limited. 2pr's "imitation writing + AI interview" mechanism is more relevant to the LinkedIn context than the general LLM, and there is no risk of account suspension.
• Content Agency Operations/Agency: The multi-account independent style and collaboration functions of the Multi-profile solution directly match the working mode of the agency. The unlimited number of members design allows team expansion without additional costs.
• B2B Marketers: Need to align LinkedIn content with broader marketing strategies, TOFU/MOFU/BOFU layered analytics provide quantifiable performance tracking.

Does not fit boundaries:

• LinkedIn is not a core platform user (e.g. mainly for TikTok/Instagram creators) - 2pr’s vertical binding means no usability outside the LinkedIn ecosystem.
• Scenarios that require in-depth long articles or serious research content - 2pr is good at the "social media hook + story + interaction" structure, which is not suitable for white papers or academic writing.
• Industries with extremely high compliance requirements for content originality (such as financial compliance, medical claims) - the copyright boundaries of AI-generated content are still in a legal gray area, and it is recommended to publish them after manual review.
• Users who rely on browser extensions for LinkedIn automation - 2pr is completely based on the official API and is not compatible with cookie/simulated click type automation needs.

Summary and Outlook

2pr's core competitiveness lies in the vertical depth of the "LinkedIn full-link AI Agent": from topic discovery to imitation writing, from scheduled publishing to interactive replies, from effect analysis to strategy optimization, it covers the entire workflow of a LinkedIn creator. Its imitation voice engine and password-less access to the official API solve the two core anxieties of LinkedIn tool users - "the content does not look like what you wrote" and "the account is subject to risk control". The introduction of the MCP protocol allows technical users to embed it into larger AI orchestration systems.

Current limitations and uncertainties: Version iterations focus on the function overlay period, and the stability of basic functions (especially the accuracy of the MCP interface and multi-account analysis panel) requires longer verification. Enterprise-level solutions lack public SLA and audit terms, and high-compliance industries require manual verification. In addition, policy changes to LinkedIn's official API may impact the scope of 2pr's core capabilities.

Purchase/Adoption Risk Assessment: Individual creators can start a trial with an annual payment plan of $24/month, and the 7-day trial period is enough to evaluate whether the imitation effect meets expectations. Institutional customers should first run the complete process on one customer account and record ROI data before expanding to other accounts. For teams that rely on 2pr as a business-critical dependency (such as operating an agency for core delivery), it is recommended to maintain a manual alternative process and pay attention to the potential impact of LinkedIn API changes on platform functionality. In the MCP integration scenario, it is necessary to limit the max_steps and set the confirmation point to prevent the AI ​​Agent from misoperation and irreversible release behavior.

Related tools: crewai, langchain

Version Info

• 2pr.io v2.0 ：v2.0 introduces complete AI interview content generation, multi-version draft comparison LinkedIn Carousel generator MCP protocol support, improved analysis panel and team collaboration capabilities. （~2025-05）
• initial public version ：The initial version focuses on LinkedIn content creative discovery and AI-assisted writing, and supports basic scheduling and comment interaction functions. Officials have not disclosed earlier iteration logs. （~2025-01）