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by tsvillain

deprecation-mcp

A free, open MCP server for checking whether a vendor API or SDK is active, deprecated, or sunset — so an agent doing upgrade/maintenance work can check before it breaks, instead of after.

API/SDK deprecations are scattered across changelog pages, RSS feeds (if you're lucky), and Sunset/Deprecation HTTP headers (if the vendor bothers implementing RFC 8594). This server puts a curated, hand-verified answer behind one tool call.

No payment gating, no metering, no billing code of any kind — this is a plain open MCP server.

What it exposes

One tool, check_deprecation:

check_deprecation(provider: string, target: string) -> {
  status: "active" | "deprecated" | "sunset" | "unknown",
  deprecated_on: string | null,
  sunset_on: string | null,
  replacement: string | null,
  migration_url: string | null,
  source_url: string,
  last_verified_at: string
}

status: "unknown" (with a blank source_url) is returned for any provider/target not in the curated dataset below — it means "not tracked", not "confirmed active."

Related MCP server: docpilot-mcp

Curated dataset

Ten provider APIs/SDKs, each checked against the vendor's own published page (source_url) on the date in last_verified_at. Data lives in data/deprecations.json.

provider

target

status

aws

aws-sdk-js-v2

sunset

stripe

sources-api

deprecated

twilio

programmable-chat

sunset

github

dependency-graph-sbom-sync

deprecated

openai

assistants-api

deprecated

slack

classic-apps

deprecated

sendgrid

v2-mail-send

deprecated

shopify

rest-admin-api

deprecated

auth0

rules-and-hooks

deprecated

paypal

nvp-soap-api

deprecated

Lookups are case-insensitive and also match each record's aliases (e.g. aws/aws-sdk resolves to aws-sdk-js-v2).

Run it

npm install
npm run build
npm start        # starts the stdio MCP server

Add to an MCP client

Claude Code (.mcp.json in your project, or claude mcp add):

{
  "mcpServers": {
    "deprecation": {
      "command": "node",
      "args": ["/absolute/path/to/deprecation-mcp/dist/index.js"]
    }
  }
}

Any other stdio-based MCP client config follows the same shape: run node dist/index.js as the server command.

Worked example

Once connected, an agent calls:

{
  "name": "check_deprecation",
  "arguments": { "provider": "aws", "target": "aws-sdk-js-v2" }
}

and gets back:

{
  "status": "sunset",
  "deprecated_on": "2024-09-08",
  "sunset_on": "2025-09-08",
  "replacement": "AWS SDK for JavaScript v3",
  "migration_url": "https://docs.aws.amazon.com/sdk-for-javascript/v3/developer-guide/migrating-to-v3.html",
  "source_url": "https://aws.amazon.com/blogs/developer/announcing-end-of-support-for-aws-sdk-for-javascript-v2/",
  "last_verified_at": "2026-08-08"
}

Tests

npm test   # builds, then runs node:test against the lookup logic

Updating the dataset

Edit data/deprecations.json directly — no build step or scraper needed, it's read at server startup. Each record needs a real source_url you actually checked and an accurate last_verified_at. When you re-verify a record, recompute its content_hash too (see below).

Drift detection

Hand-checking ten source_urls every so often doesn't scale, and stale data is worse than no data. A weekly GitHub Action (.github/workflows/check-drift.yml) fetches each record's source_url, hashes the response body (sha256), and compares it to the content_hash stored on the record at last_verified_at. If the hash changed, the page changed since it was last verified — the record is flagged, not auto-updated. The automation never writes to data/deprecations.json; a changed page only means "a human or agent needs to re-verify this record by hand," never an inferred new status. Wrong auto-inferred status is worse than no automation.

When drift or a fetch failure is detected, the workflow opens (or updates) a single GitHub issue labeled drift-check summarizing which records need attention; it closes that issue automatically once a later run comes back clean.

Run it locally:

npm run build
npm run check-drift

Exits 0 if every record's hash still matches, 1 otherwise.

All ten source_urls were fetched with a plain GET (no headless browser, no bot-protection workaround) when their content_hash baselines were seeded, and all ten succeeded. If a vendor later adds bot protection or a redirect that breaks the plain-GET fetch, that record will show up as fetch_failed in the weekly report rather than being silently skipped.

Known limitation: the AWS blog post, Stripe docs page, and PayPal docs page (aws/aws-sdk-js-v2, stripe/sources-api, paypal/nvp-soap-api) embed per-request dynamic content — a nonce, timestamp, or session token that changes on every fetch even when the substantive page content hasn't. Their body hash is therefore not fully stable across requests, and the weekly check may occasionally flag one of these three as "drifted" even with no real change. This is disclosed rather than worked around (e.g. by stripping known-volatile substrings): a false-positive "please go look at this page" is an acceptable cost for a tool whose entire design principle is to never guess at a status. A human/agent re-verifying such a flagged record should expect it may be a false alarm.

Available Tools

1 tool
check_deprecationCheck API/SDK deprecation statusA

Look up whether a provider's API or SDK is active, deprecated, or sunset. Covers a curated set of high-traffic providers (Stripe, Twilio, AWS, GitHub, OpenAI, Slack, SendGrid, Shopify, Auth0, PayPal). Returns 'unknown' for anything not tracked.

ParametersJSON Schema
NameRequiredDescriptionDefault
targetYesAPI/SDK identifier within that provider, e.g. 'sources-api'
providerYesVendor slug, e.g. 'stripe', 'aws', 'github'

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does well by disclosing the main behavior: returns a status of active/deprecated/sunset, covers a specific provider set, and has a defined fallback ('unknown') for untracked entries. This gives users a realistic expectation of tool coverage and output. It stops short of discussing potential errors or data freshness, but for a lookup tool this is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, using just two sentences to convey the core function, scope, and fallback behavior. Every word adds value, and the key information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter lookup tool with no output schema, this description adequately covers the essential aspects: what it does, which providers it covers, and what it returns for untracked providers. It lacks detail on the meaning of each status or any potential limitations, but the description is otherwise complete enough for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already has 100% descriptive coverage for both parameters (provider, target), including examples. The description adds no additional parameter-level context beyond what the schema provides, so it does not exceed the baseline expectation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('look up'), resource ('provider's API or SDK'), and the possible outcomes (active, deprecated, sunset). It also explicitly lists covered providers, which adds scope clarity and distinguishes it from potential sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use the tool by specifying the curated provider list and noting that untracked providers return 'unknown'. It implicitly indicates this should be used for deprecation checks on those providers, though it does not explicitly contrast with alternatives or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev0.1.0
    • First observedcheck_deprecation

TDQS

A4.3/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion. The tool has a clear, specific purpose: querying deprecation status for known providers.

Naming Consistency5/5

A single tool name is inherently consistent. 'check_deprecation' follows a clear verb_noun pattern and accurately describes the action.

Tool Count4/5

One tool is slightly below the typical 3-15 range, but it is perfectly suited to the server's narrow purpose of checking deprecation status. The scope does not feel artificially limited.

Completeness4/5

The core lookup operation is fully covered. A minor gap is the absence of a way to programmatically list supported providers; the agent must rely on the static description to know which providers are tracked.

Maintenance

ActivitySlowing
ResponsivenessUnresponsive

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