Cacheflow MCP. Manage proposals and sync data from a single conversation.
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Cacheflow MCP Server handles your entire proposal-to-cash cycle. It lets you create new proposals, check approval statuses, retrieve detailed quotes, and sync data to CRM—all via natural conversation.
Stop manually checking statuses; manage your entire sales pipeline directly through your AI client.
What your AI agents can do
Create proposal
Creates a brand-new sales proposal using required input data.
Get approval requests
Lists all pending internal approvals that require your review.
Get proposal details
Fetches specific, deep metadata for a single, existing proposal ID.
You pass the necessary data as a JSON string, and the server creates a complete, actionable sales proposal.
The server returns a list of all active proposals, including their current status (sent, viewed, signed).
You input a proposal ID, and the server gives you detailed metadata on that single proposal.
The server shows all internal approval requests awaiting your sign-off, maintaining the sales pipeline.
The server lists external customers synced into Cacheflow from your connected CRM.
You trigger the transfer of proposal data, updating records in your connected CRM like Salesforce or HubSpot.
Ask AI about this MCP
Supported MCP Clients
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Cacheflow MCP Server: 6 Tools for Sales Automation
These tools let your AI client create proposals, track approvals, list customers, and push data to your CRM without leaving your chat window.
019dd0c8create proposal
Creates a brand-new sales proposal using required input data.
019dd0c8get approval requests
Lists all pending internal approvals that require your review.
019dd0c8get proposal details
Fetches specific, deep metadata for a single, existing proposal ID.
019dd0c8list customers
Retrieves the complete directory of external customers synced from your connected CRM.
019dd0c8list proposals
Lists all current sales proposals and their status (sent, viewed, signed).
019dd0c8sync to crm
Pushes the selected proposal data to your connected CRM system.
Choose How to Get Started
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Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
The Cacheflow MCP Server handles your whole proposal-to-cash cycle. Your AI client lets you build new proposals, check approval statuses, pull detailed quotes, and sync everything to your CRM—all just by talking to it. You don't gotta manually check statuses anymore; you manage your whole sales pipeline through your agent.
create_proposal: You give it the necessary data, and the server builds a brand-new, actionable sales proposal.
list_proposals: It gives you a list of all your active sales proposals, showing their current status whether they're sent, viewed, or signed.
get_proposal_details: If you know a proposal ID, this tool pulls all the deep metadata for that specific proposal.
get_approval_requests: It shows every internal approval request that's waiting for your sign-off, keeping the deal moving.
list_customers: It pulls the full directory of external customers that are synced into Cacheflow from your connected CRM.
sync_to_crm: You trigger this to push the selected proposal data straight to your connected CRM system, updating records there.
How Cacheflow MCP Works
- 1 First, you subscribe to the server and retrieve your API Key and Subdomain from Cacheflow.
- 2 Next, you direct your AI client to the server. You use natural language to tell your agent what you need—for example, 'List all active proposals.'
- 3 The server executes the relevant tool (like
list_proposals) and returns the structured data directly to your AI client for review.
The bottom line is you manage the entire proposal-to-cash cycle conversationally through your AI client, without leaving your workspace.
Who Is Cacheflow MCP For?
This server is for Sales Ops Leads, Account Executives, and Finance Teams. If your job involves turning quotes into signed contracts and ensuring that data lands correctly in the CRM, this is for you. It eliminates the painful, repetitive cycle of manual status checks and data handoffs.
Retrieves proposal summaries and checks approval statuses using natural language commands to maintain pipeline velocity.
Automates creating professional quotes and triggering CRM syncing without leaving their primary workflow.
Monitors the transition from a draft proposal to an active checkout using simple AI queries, maintaining audit trails.
What Changes When You Connect
- Automate the quoting process with
create_proposal. You feed the data, and the server generates the entire proposal, skipping the manual drafting stage. - Keep track of deals using
list_proposals. You instantly see which proposals are sent, which are viewed, and which are awaiting a signature, eliminating status sheet guesswork. - Keep your data clean by using
sync_to_crm. You trigger the data push to Salesforce or HubSpot, ensuring your CRM records are always current and accurate. - Accelerate internal reviews with
get_approval_requests. You get real-time visibility into who signed off on what, keeping your sales cycle moving fast. - Gain context with
list_customers. You pull the complete directory of external customers synced from your CRM, so you never lose visibility on who you're talking to. - Deep-dive into any deal with
get_proposal_details. You retrieve specific, detailed metadata on a single proposal, giving you the full audit trail instantly.
Real-World Use Cases
A new deal needs a quote.
The AE identifies a potential client. Instead of opening a separate quoting tool, they ask their agent to run create_proposal with the client's requirements. The agent returns a complete, structured quote ready to send, eliminating the initial setup time.
The sales cycle is stuck on approvals.
The Sales Ops Lead needs to know why a deal hasn't moved. They ask the agent to run get_approval_requests. The agent identifies the bottleneck (e.g., 'VP signature needed') and provides the exact ID, allowing the lead to follow up immediately.
Proposal data needs to hit the CRM.
After a client signs, the AE needs to update HubSpot. They prompt the agent to run sync_to_crm. The agent initiates the data push, updating the deal record automatically and confirming the sync status.
Need to check the status of 20 proposals.
Instead of opening the dashboard and clicking through 20 proposals, the user asks the agent to run list_proposals. The agent returns a consolidated list, showing status and metadata for all 20 deals at once.
The Tradeoffs
Manual status tracking
Opening the Cacheflow dashboard, navigating to the proposals tab, and manually checking the status of 15 deals one by one. This takes 10 minutes and misses nuances.
→
Ask your agent to run list_proposals. It compiles the status of all deals into one response, letting you see if they're viewed or signed without clicking anything.
Forgetting to sync data
A deal is signed, but the admin forgets the final step of running the sync job, leaving the CRM record inaccurate and out of date.
→
Prompt your agent to run sync_to_crm immediately after signing. This ensures the data push to the CRM is triggered right away, keeping your records accurate.
Building quotes piecemeal
Creating a draft quote in one tool, then copying the pricing into a spreadsheet, and finally manually entering it into the CRM. This is slow and prone to errors.
→
Use create_proposal. This tool handles the entire quoting process and structuring the data for you. Then, follow up with sync_to_crm to get it into the CRM.
When It Fits, When It Doesn't
Use this server if your core bottleneck is the handoff between quoting, internal approval, and CRM record keeping. You need to turn a multi-system, multi-person process into a single, conversational API call. You should use it when you need to know 'What is the current state of this deal?'
Don't use it if your primary need is pure data storage or simple file retrieval. If you just need to look at raw historical data not tied to a proposal lifecycle, a general database query tool will work better. If you only need to send simple messages, a messaging tool is better. Cacheflow is for the structured, high-stakes process of making money.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cacheflow. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 6 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
The deal closing process shouldn't require opening three different apps.
Today, closing a deal means juggling three systems: the quoting tool, the approval dashboard, and the CRM. You build the proposal in one place, check the status in another, and then copy-paste the final numbers into the third. It's a copy-paste nightmare that kills momentum.
With the Cacheflow MCP Server, you keep it all in your agent chat. You tell your AI client to 'List all proposals for Acme.' It runs `list_proposals` and gives you the status, the details, and the next steps—all in one response. No switching tabs required.
Cacheflow MCP Server: Manage proposals and sync data.
You no longer have to manually run sync jobs or check dashboards. Your agent handles the sequence. You tell it to finalize the deal, and it orchestrates the calls: it validates the data via `get_proposal_details`, triggers the necessary internal approvals via `get_approval_requests`, and finally runs `sync_to_crm`.
It’s not just about getting data; it’s about ensuring the data is in the right place, at the right time. Your agent coordinates the entire flow. Period.
Common Questions About Cacheflow MCP
How do I use the `list_proposals` tool with Cacheflow MCP Server? +
You simply ask your agent to list all active proposals. The server runs list_proposals and returns a list showing the proposal ID, the customer, and its current status (sent, viewed, signed). You can then ask for more details on a specific ID.
Does `sync_to_crm` update Salesforce or HubSpot? +
Yes, the sync_to_crm tool pushes the proposal data to your connected CRM instance, including Salesforce or HubSpot. This keeps your deal records current with the latest status.
What is the best way to check my pending approvals using `get_approval_requests`? +
Just tell your agent, 'Show my pending approval requests.' The server runs get_approval_requests and gives you a list of pending items, detailing which department or person needs to sign off.
Can I create a proposal without knowing the customer's ID? (create_proposal) +
You must provide the necessary JSON data for the create_proposal tool. The tool requires specific data fields to build a valid, structured quote.
How do I get deep details on a specific proposal ID using `get_proposal_details`? +
Specify the proposal ID and ask the agent to retrieve the details. The server then runs get_proposal_details and returns the full metadata, giving you the complete history and context for that deal.
How do I list all customers using the `list_customers` tool? +
You pass no arguments to list_customers. It returns a directory of external customer records synced from your CRM. This lets your agent maintain a coordinated view of your entire client base.
What happens if I try to sync a proposal with `sync_to_crm`? +
The sync_to_crm tool triggers a data push to your connected CRM instance. If the proposal ID is valid, your deal records update automatically. If the proposal data is missing, the sync fails, and the agent reports the error.
Can I create a new proposal using `create_proposal`? +
Yes, create_proposal creates a new sales proposal. You must pass the necessary data as a JSON string to define the contents, customer, and pricing details for the proposal.
How do I find my Cacheflow API Key? +
Log in to your dashboard, navigate to Settings > API, and generate or copy your secret access token.
What is my subdomain in Cacheflow? +
Your subdomain is the first part of your Cacheflow URL. For example, if you access at acme.getcacheflow.com, your subdomain is acme.
Can I trigger a CRM sync via AI? +
Yes! Use the sync_to_crm tool and provide a specific proposal ID to immediately push data to your connected Salesforce or HubSpot instance.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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