Custom Context MCP Server

Created By
omer-ayhana year ago
This Model Context Protocol (MCP) server provides tools for structuring and extracting data from text according to JSON templates.
Overview

What is Custom Context MCP Server?

The Custom Context MCP Server is a Model Context Protocol (MCP) server designed to provide tools for structuring and extracting data from text according to JSON templates.

How to use Custom Context MCP Server?

To use the server, install the necessary dependencies with npm install, then run the server using npm start. For development with hot reloading, use npm run dev:watch.

Key features of Custom Context MCP Server?

  • Text-to-JSON transformation for structured data extraction
  • Grouping and structuring text based on JSON templates
  • Support for arbitrary JSON structures with nested placeholders
  • Intelligent extraction of key-value pairs from text
  • Custom hot reloading setup for development

Use cases of Custom Context MCP Server?

  1. Structuring AI-generated text into JSON format for data analysis.
  2. Automating data extraction from unstructured text sources.
  3. Facilitating integration of AI outputs into downstream applications.

FAQ from Custom Context MCP Server?

  • What is the purpose of the MCP server?

The MCP server helps in structuring and extracting data from text using predefined JSON templates.

  • Is there a specific format for JSON templates?

Yes, templates can include placeholders defined with angle brackets and must be valid JSON strings.

  • Can I use this server for any type of text?

Yes, the server is designed to work with any text that can be structured according to the provided JSON templates.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
omer-ayhan
Star
0
Language
TypeScript
License
MIT license

Recommend Servers

View All
Voyei

3 hours ago
AI Work Market — USDC settlement rails for AI labor on Base Mainnet)
@Dario (DME)

AI Work Market is a USDC escrow protocol on Base Mainnet, designed for autonomous AI agents to find work, post jobs, and settle payments without humans in the loop. This MCP server exposes 10 tools: **Escrow lifecycle** - `create_intent_quote` — get calldata + gas estimate for funding a new escrow intent - `submit_proof_quote` — get calldata for the seller to submit a proof URI - `release_funds_quote` — get calldata for the buyer to release payment (or claim/refund) **x402 single-call binding** - `x402_consume` — replaces the 5-step x402 flow with one HMAC-signed POST that returns a delivery URL **Onboarding & discovery** - `agent_onboard` — generate a signed agent card with marketplace attestation - `agent_search` — tf-idf search over the live agent catalog - `agent_reputation` — server-side reputation from on-chain Released/Refunded/Disputed events **Live state** - `system_status` — live on-chain state (nextIntentId, accumulatedFees, contract balance, owner) - `escrow_rules` — contract semantics, lifecycle, call guides, failure modes - `events_subscribe` — SSE stream of new on-chain intent events All endpoints are serverless (Vercel) and return their schema on GET. No browser, no wallet UI required for an agent to integrate. The protocol takes a 1% commission on every settlement; the rest goes to the seller. The full AgentCard is at `/.well-known/agent-card.json` (A2A-compatible). The OpenAPI 3.0.3 spec is at `/.well-known/openapi.json` with `components.securitySchemes` (none, hmacX402). `robots.txt` allows GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, Applebot-Extended, CCBot, Amazonbot.

13 hours ago