
MCP is one view of a capability table, and the view you pick costs 6.25x
The Model Context Protocol (MCP) is a way of describing a set of capabilities to a model. It is not the place those capabilities live, and it is not the thing that runs them. On this site the capabilities live in one database table — one row per capability — and MCP is one of three ways that table is shown to a model.
A projection here means exactly one thing: a view generated from a table, holding nothing of its own. Change the table and every view changes in the same instant. Delete a view and nothing is lost. Below, the plainer word surface is used wherever it reads more clearly; they mean the same thing.
The three surfaces reach the same capability catalogue. The recorded benchmark puts 6.25× between the cheapest and the dearest turn.
Evidence status
Observed marks first-party measurements or runtime receipts from the named environment. Derived marks arithmetic calculated from cited inputs. Specified marks vendor or standards documentation. Implemented and deployed name code and live-state evidence, respectively. Reproduced means the stated procedure was rerun. Externally attested marks operator reports; those reports show that an experience occurred, not that it is universal.
MCP at the wire is JSON-RPC 2.0, one of two transports, and a handful of method names
A reader who has never opened the specification can hold the whole thing in one paragraph. A client and a server exchange JSON-RPC 2.0 messages. JSON-RPC is a remote-procedure-call format: a JSON object carrying jsonrpc, method, params and id, answered by an object carrying the same id and either result or error. The specification is blunt about this: "MCP uses JSON-RPC to encode messages. JSON-RPC messages MUST be UTF-8 encoded."
Those messages travel over one of two transports. Standard input and output, for a server running as a local subprocess. Or HTTP POST, for a server running somewhere else — the specification calls the second one Streamable HTTP and requires that "Every JSON-RPC message sent from the client MUST be a new HTTP POST request to the MCP endpoint." It also states a preference: "Clients SHOULD support stdio whenever possible."
The method names that matter for a capability catalogue are four:
| Method | Direction | What it carries | What this site's server returns |
|---|---|---|---|
initialize | client → server | protocol version, client capabilities | protocolVersion: "2025-06-18", capabilities: {"tools":{"listChanged":false}}, serverInfo |
tools/list | client → server | nothing, or a pagination cursor | an array of {name, description, inputSchema} — 831 of them, measured below |
tools/call | client → server | params.name, params.arguments | {content:[{type:"text",text:"…"}], isError:false} |
notifications/tools/list_changed | server → client | nothing | never sent — this server declares listChanged: false |
A tool definition is three fields: a name, a description in prose, and a JSON Schema for the arguments. That triple is what lands in the model's context window. Everything expensive about MCP follows from the size of that triple multiplied by the number of tools.
What MCP is not
- Not a wire protocol. The layering claim gets used to wave away responsibility, and it is wrong. JSON-RPC is the wire protocol; MCP sits above it.
- Not a place capabilities live. A server holds handlers. Nothing in the specification says where the list of capabilities is stored, or that it must be a hand-written list at all.
- Not a rule about context loading. The tools specification says implementations "are free to expose tools through any interface pattern that suits their needs—the protocol itself does not mandate any specific user interaction model." Every token figure quoted below is a property of a client, not of the protocol.
- Not a replacement for an API. It is a second face on one. The endpoint stays; MCP is a decorated index in front of it.
One recorded 891-row catalogue cost 6.25× more through its largest surface
The table holds 891 rows — 876 objects answered the live registry today, and the drift is explained under the measurements. Each row is a full capability contract: key, runner, target, documentation, input schema, authority flags. What a directory row is covers the row itself; 891 tools, zero tool schemas covers why a catalogue is better held as data than as code.
| Surface | Tool definitions in the model's context | What the model can reach | What the client must support | Measured input tokens per turn | Measured cost per turn | What breaks |
|---|---|---|---|---|---|---|
Protocol only — POST /api/dispatch | 0. The 9 definitions present are the client's own built-ins | all 891 rows | an HTTP client. No MCP, no tool calling at all | 14,071 | $0.00456265 | the model must be told four endpoints once; no client UI enumerates the catalogue |
Small surface — workers/mcp-server | 7 tools, whatever the catalogue size | all 891 rows, through the dispatch tool | an MCP client | not measured | not measured | a client that lists tools shows seven generic entries; discovery becomes a call, not context |
Per-row MCP — POST /api/mcp | 831 measured today, 856 recorded | 831 rows, each a named tool | an MCP client | 149,187 | $0.02852109 | prompt cost, tool-selection accuracy, and strict-schema clients rejecting the whole list |
| Per-row MCP, tool search on | 9 plus a ToolSearch tool | all 891, loaded on demand | a client with deferred tool loading | 14,109 | $0.00443075 | the deferred index does not cover every server — two filed bugs below |
The arithmetic between the first and third rows: 149,187 − 14,071 = 135,116 input tokens burned per turn holding definitions the turn mostly does not use. 149,187 ÷ 14,071 = 10.6× the input tokens. $0.02852109 ÷ $0.00456265 = 6.25× the money. Across a thousand turns that gap is $23.96. The token ratio and the money ratio differ because output tokens are in both bills and the cache behaves differently; both are the recorded gateway figures, not a rate derived from one of them.
Each surface is a file, and the file states its own tool count
Per-row MCP is functions/api/mcp.js, 189 lines. Lines 118–137 are the entire projection:
const r = await env.DB.prepare(
'SELECT key, type, category, content, input_schema FROM directory ' +
'WHERE IFNULL(enabled,1)=1 AND IFNULL(planner_visible,1)=1 ' +
'ORDER BY IFNULL(planner_rank,100), key'
).all();One row becomes one tool: name is the row key, description is the first documentation line plus [type · category], inputSchema is the row's schema after normalisation. Line 162 is the whole tools/list handler. Lines 80–116 exist for one reason worth stating plainly: Moonshot and Kimi clients validate every schema strictly and reject the entire tool list on the first violation, so one legacy row with a required name missing from properties would blank the catalogue for that client. Claude Code tolerates both, which is how the bad schemas accumulated unnoticed.
Small surface is workers/mcp-server/src/index.ts, 138 lines, a Cloudflare McpAgent on a Durable Object. It registers seven tools, lines 19–105:
$ grep -A1 'this.server.tool($' workers/mcp-server/src/index.ts | grep '"'
"d1_query",
"kv_get",
"kv_put",
"list_directory",
"dispatch",
"oip_registry",
"oip_invocations",Seven, not six. An earlier record of this surface counted six by folding kv_get and kv_put into one line and omitting d1_query. The file is the authority and the file says seven. The invariant is the point either way: seven tools whether the table holds 9 rows or 9,000, because dispatch takes {key, body} and the key space is the table. All seven parameter descriptions together come to 429 characters of source.
Protocol only is functions/api/dispatch.js. No tool definitions are published anywhere. A model that can make an HTTP request resolves an intent, reads a contract, invokes it, and reads a receipt — four calls, set out in Resolve, read, invoke, receipt.
Measured today: 831 definitions occupied 434,636 bytes on the wire
Two first-party measurements, both rerunnable. MCP_TOKEN is the server's bearer token; /api/mcp accepts it in Authorization or in x-mcp-token.
Measurement 1 — count the per-row surface.
curl -s -X POST https://miscsubjects.com/api/mcp \
-H "Authorization: Bearer $MCP_TOKEN" \
-H 'content-type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' -o tl.json \
-w "http=%{http_code} bytes=%{size_download} time=%{time_total}s\n"
python3 -c "import json;t=json.load(open('tl.json'))['result']['tools'];print(len(t), len(json.dumps(t)))"Three readings on 2026-07-26:
| Reading (UTC) | Tools | JSON bytes | What was counted | Wall time |
|---|---|---|---|---|
| 04:37:06Z | 833 | 452,157 | Python re-serialization with spaces | not recorded |
| 04:39:08Z | 831 | 451,197 | Python re-serialization with spaces | 0.60 s |
| 05:03:04Z | 831 | 434,636 | exact HTTP response body | 0.267 s |
The HTTP body contains 434,592 bytes of compact tool definitions plus the 44-byte JSON-RPC wrapper. Python's default json.dumps adds spaces after separators, which is why the command above reports 451,197 for the same 831 definitions. Both numbers are reproducible; 434,636 is the network payload.
Where the 451,197-character Python serialization goes, computed from the same file:
| Component of the tool list | Characters | Share |
|---|---|---|
Descriptions — first doc line plus [type · category] | 200,757 | 44.5% |
| Input schemas, after normalisation | 189,354 | 42.0% |
| Tool names | 13,862 | 3.1% |
| JSON structure and quoting | 47,224 | 10.5% |
Compact average per tool: 523 bytes. Largest single definition in the spaced Python serialization: CF_OBSERVABILITY_QUERY_WORKER_OBSERVABILITY at 6,511 bytes. By runner type the 831 split into 462 fn, 301 http, 50 flow, 18 agent.
Three counts for the same server now exist on this page — 856 recorded, 833 at 04:37, 831 at 04:39 — and each is correct for its moment. Rows get added, disabled (enabled = 0) and hidden (planner_visible = 0) while the site runs, and only enabled plus planner-visible rows are projected. A tool count taken from an MCP server is a reading, not a constant. The 891 total and the 856 projection were taken on 2026-07-25.
Measurement 2 — show that zero definitions still reaches everything.
curl -s "https://miscsubjects.com/api/dispatch?registry=1" -o reg.json \
-w "http=%{http_code} bytes=%{size_download} time=%{time_total}s\n"
python3 -c "import json;print(json.load(open('reg.json'))['count'])"
curl -s "https://miscsubjects.com/api/dispatch?ask=send%20an%20email" | head -c 400Result at 05:03:04Z: http=200 bytes=1606794 time=0.397555s, and 876 objects. The resolver call returned {"protocol":"OIP","version":"1.2.0","kind":"ask","question":"send an email","count":12,"best":{"key":"EMAIL_SEND", …}} in 14,481 bytes — twelve candidate capabilities ranked, one recommended, none of it resident in a prompt. Nothing was registered with a model. No tool definition was loaded. All 876 objects are invokable by key.
The case for shipping an MCP surface, at its strongest
The deflationary reading — MCP is a REST API with extra steps — is usually stated by people who then keep using it. CharlieDigital, whose team built one, put the deflation and the recommendation in a single sentence: "MCP is effectively \"just another HTTP REST API\"; OAuth and everything. The key parts of the protocol is the communication shape and sequence with the client, which most SDKs abstract for you". Deploying one is no harder than deploying the API underneath it, because the SDK writes the transport.
brookst gave the sharpest rebuttal of the just-HTTP framing: "It's like saying APIs are dead because you can just use HTTP. They're not the same thing, though of course you can hand-roll the higher layer in the lower one. It's just more work, less standard, less valuable." A decorated index of features beats a bare endpoint list, and the decoration is the product.
menix argues the contract itself is the value rather than a nicety. Input and output schemas let a code-writing agent plan one precise program instead of a print-and-inspect loop, and "Tool results from programmatic calls are not added to Claude's context window, only the final code output is. They report up to 98.7% token savings in some workflows."
827a supplies the dissent every measurement below has to survive: "The idea that MCP tool definitions take up a certain number of tokens is laughable. That's an implementation detail of the agent harness." This is correct as written, and the specification agrees — nothing in MCP says a client must paste all definitions into a prompt. The measurements are of clients. They still decide the bill, because those are the clients that exist.
There is an audience argument too. oortcrate_1 prefers a bash wrapper personally and still grants the point: MCP serves non-technical teammates who want a connection that works without filing a pull request.
The case against, with the numbers the complainants actually measured
| Who | What they measured | Verdict |
|---|---|---|
| moltar | "Right now loading GitHub MCP takes something like 50k tokens." | reduces MCP to "an API with docs"; wants progressive reveal |
| gertjandewilde (Apideck) | "tool definitions alone burned 50,000+ tokens before the agent touched a single user message" | replaced the server with a CLI at ~80 tokens; cites a 75-run comparison at 4–32× overhead |
| yonatangross | "The main agent context burns 16.9k tokens (8.5% of 200k) loading 68 MCP tool schemas at session start. Most are never called by the main agent" | publishes a per-server table; scoping and tool search were available and unused |
| abdlkrim-jribi | "The agent injects ALL 47 tool schemas on every single request, consuming ~13,341 tokens before the user message is even sent." | audits his own agent; publishes the ~4,168 / ~4,515 / ~751 / ~3,906 split |
| mjlee | "With a handful of third party MCPs I've seen tens of thousands of tokens used before I've started anything." | finds MCP beneficial anyway |
| 0xbadcafebee | "Say each tool is 150 tokens, that's 150 50, or 7500 tokens, dumped into the beginning of every session."* | the balanced account — shell one-liners are more non-deterministic, so re-runs pollute context too; uses both |
| locknitpicker | "Skills effectively turned MCPs obsolete in the vast majority of MCP applications." | a progressive-disclosure CLI needs no skill file at all |
| noodletheworld | "MCP is just \"me too\"; people want MCP to be an \"AI App Store\"; but the blunt, harsh reality is that it's basically impossible to achieve that dream" | if you want an app, build an app |
Two mitigations get proposed against all of this, and both have filed defects. cheema33 pre-empts the first: "And no, the tool search function recently introduced by Anthropic does not completely solve this problem." Anthropic's own documentation puts that mitigation at "over 85 percent" reduction on a five-server setup consuming "~55k tokens in definitions before Claude does any work" — real, and not total. sophiabits names the second-order cost of the other mitigation, loading servers lazily per task: "The main problem with this approach at the moment is it busts your prompt cache, because LLMs expect all tool definitions to be defined at the beginning of the context window."
Deferred loading has its own failure modes on record. In anthropics/claude-code#57033, servers added at claude.ai show Connected in /mcp and yet "Any ToolSearch query that should match a claude.ai MCP tool returns zero results". In openai/codex#24536, "codex exec can silently finish with no assistant message when an explicitly configured MCP tool is deferred behind tool_search." A silent empty turn is worse than an expensive one.
Round trips are the argument that survives bigger context windows
Token cost is a moving target. Context windows grow, caches improve, tool search lands. The structural argument does not move, and it is a different argument.
A tool call happens between completions. The model stops, the client executes, the result comes back, the model starts again. DonHopkins names the difference: "I call this \"speed of light\" as opposed to \"carrier pigeon\"." Code the model writes loops, recurses and composes inside one generation.
martinald gives the worked case — summing 150 order IDs. "With MCP the agent would have to do 150 tool calls and explode your context." One scripted loop does it in one round trip at roughly one percent of the tokens. He also notes there is no reason a harness could not expose MCP tools inside a sandboxed code environment, and that nobody does.
Two vendors have published the same finding independently. Anthropic: "This reduces the token usage from 150,000 tokens to 2,000 tokens—a time and cost saving of 98.7%." Cloudflare, on the same pattern: "With the traditional approach, the output of each tool call must feed into the LLM's neural network, just to be copied over to the inputs of the next call, wasting time, energy, and tokens. When the LLM can write code, it can skip all that, and only read back the final results it needs."
What that implies for exposing a catalogue is concrete, and it is not "abandon MCP":
- Expose one invoking tool that takes a key and arguments, not one tool per capability. That is what the seven-tool surface does.
- Make discovery a call that returns data —
list_directory, or the protocol's resolver — so the catalogue is paged through rather than resident. - Keep an HTTP path a code-execution sandbox can hit directly, so a loop over 150 items is one round trip instead of 150.
solarkraft supplies the honest floor under all three: every capability costs some context, because the model has to know it exists in order to invoke it. The only question is whether it costs 523 compact bytes each or one line in a search result.
notifications/tools/list_changed is in the specification, and named clients ignore it
The advertised benefit of a server-side catalogue is that adding a capability needs no client redeploy. The specification supplies the mechanism: "When the list of available tools changes, servers that declared the listChanged capability SHOULD send a notification" — notifications/tools/list_changed, a JSON-RPC notification with no parameters and no reply.
Whether that works depends on the client honouring it, and three filed reports say several do not:
| Client or system | Filed | Verbatim |
|---|---|---|
Kiro IDE — kirodotdev/Kiro#6553, closed | 2026-03-20 | "When an MCP server dynamically adds or removes tools at runtime and sends this notification per the MCP spec, Kiro IDE does not re-query tools/list, so the new tools never appear until the server is manually reconnected." |
GitHub Copilot CLI — microsoft/wassette#308, open | 2025-09-29 | "Internal terminal testing shows the CLI never refreshes its tool list, unlike GitHub Copilot in VS Code which updates immediately." |
MCPJungle gateway — mcpjungle/MCPJungle#260, open | 2026-05-15 | "MCPJungle caches upstream tool lists at registration time only. If an upstream server adds or removes tools later, MCPJungle's view stays stale until a manual re-registration or full restart." |
The wassette report comes from a Microsoft engineer with a reproduction video, and notes the same server updates immediately in VS Code — so the defect is per-client, not per-spec.
This site's per-row server sidesteps the question by declaring the truth instead of a promise. Line 159 of functions/api/mcp.js returns capabilities: {"tools":{"listChanged":false}}. A new row is live on the protocol surface the instant it is written, and appears on the MCP surface the next time a client calls tools/list — which, for most clients, is at connect. "Add a capability without a redeploy" is true of the table and false of the client. Say the second half out loud or the sentence is a lie.
Verdict: publish MCP when the client is not yours, publish the protocol when it is
- Do publish an MCP surface when the consumer is a client you do not control and cannot teach — Claude Desktop, Cursor, ChatGPT connectors, a colleague's IDE. There is no other way in. Publish it as a small surface: one
dispatch-style tool plus a discovery tool. Never one tool per row. - Do publish a per-row surface only when a client must literally see named tools in its own interface, and only with that client's deferred loading switched on. Otherwise expect the bill: 149,187 input tokens and $0.02852109 per turn, measured.
- Do not put MCP in front of your own agent when you already control the harness. The protocol surface reached all 891 capabilities at 14,071 input tokens and $0.00456265 per turn, with nine tool definitions in context — all nine of them the client's built-ins.
- Do not treat MCP as the architecture. It is a view. The table is the thing.
What would change this verdict. A mainstream client that fetches definitions on demand rather than at connect, and honours notifications/tools/list_changed, would collapse the per-row surface's cost to roughly the protocol's and remove the reason to hand-build a small surface. Anthropic's tool search is the first move in that direction and already reaches 14,109 tokens on this catalogue — within 0.3% of the protocol-only figure. Two filed bugs, claude-code#57033 and codex#24536, say it is not yet reliable enough to depend on. When those close and the behaviour is the default rather than a flag, publish per-row and stop hand-rolling.
Publish the same catalogue three ways
Cheapest surface first, because it is also the one that works everywhere.
A. Protocol only — no server to write. Prerequisite: a capability table with a key, a runner, a target, a documentation field and an input schema (see the row contract), plus one HTTP handler that looks a key up and runs it.
GET /api/dispatchreturns a manifest naming the verbs and endpoint shapes. It was 17,404 bytes at 05:06:05Z.GET /api/dispatch?ask=<intent>returns ranked candidates, each with anexample, anexample_argsand a readyrun_nowURL.GET /api/dispatch?key=<KEY>&format=markdownreturns the exact row contract.POST /api/dispatchwith{"key":"KEY","body":"args"}invokes it. Add"shape": truefor a dry run that returns the fully-shaped outbound payload without firing.GET /api/dispatch?receipt=<id>returns the receipt.
Run the read-only TIME_NOW path end to end:
export TERMINAL_KEY="<owner access key>"
curl -sS "https://miscsubjects.com/api/dispatch?ask=what%20time%20is%20it" \
| jq '{count, best: .best.key}'
# {"count":12,"best":"NOW"}
curl -sS "https://miscsubjects.com/api/dispatch?key=TIME_NOW&format=markdown" \
| sed -n '1,12p'
# begins: ## §SELF — miscsubjects capability (paste without context)
curl -sS -X POST "https://miscsubjects.com/api/dispatch" \
-H "x-terminal-key: $TERMINAL_KEY" -H "content-type: application/json" \
--data '{"key":"TIME_NOW","body":""}' | tee invocation.json \
| jq '{ran, result, invocation_id: .invocation.id}'
# ran is true; result contains now, today, time, zone and iso
INVOCATION_ID="$(jq -r '.invocation.id' invocation.json)"
curl -sS "https://miscsubjects.com/api/dispatch?receipt=$INVOCATION_ID" \
-H "x-terminal-key: $TERMINAL_KEY" | jq '{id, object_id, actor}'
# id equals $INVOCATION_ID and object_id identifies TIME_NOWThe live run at 05:06:05Z returned HTTP 200 for all four calls, resolved NOW, invoked TIME_NOW with ran: true, and read a 13,036-byte receipt. Tell the model these five endpoint shapes once, in a system prompt or skill file. Cost in tool definitions: zero.
B. Small surface — one file, seven tools. Prerequisite: an MCP SDK and somewhere to run it. On Cloudflare that is McpAgent from the agents package on a Durable Object, McpServer from @modelcontextprotocol/sdk, and zod for parameter schemas. Register dispatch with {key, body}, register one discovery tool that queries the table, expose /mcp for Streamable HTTP and /sse for the older transport, and gate both behind a bearer check. Working file: workers/mcp-server/src/index.ts.
The deployed server can be counted with the official TypeScript SDK:
npm install @modelcontextprotocol/sdk
export TERMINAL_KEY="<owner access key>"
node --input-type=module <<'JS'
import {Client} from "@modelcontextprotocol/sdk/client/index.js";
import {StreamableHTTPClientTransport} from "@modelcontextprotocol/sdk/client/streamableHttp.js";
const transport = new StreamableHTTPClientTransport(
new URL("https://miscsubjects-mcp.massoumi-cyrus.workers.dev/mcp"),
{requestInit:{headers:{authorization:`Bearer ${process.env.TERMINAL_KEY}`}}}
);
const client = new Client({name:"count-tools",version:"1"},{capabilities:{}});
await client.connect(transport);
const listed = await client.listTools();
console.log(listed.tools.map(tool => tool.name));
await client.close();
JSExpected output, measured at 05:04:50Z: d1_query, kv_get, kv_put, list_directory, dispatch, oip_registry, oip_invocations — seven definitions totalling 2,165 compact JSON bytes. The count stays seven when the catalogue doubles because only dispatch and the discovery calls refer to catalogue keys.
C. Per-row MCP — the compatibility surface. One SELECT, one loop, one normaliser. The normaliser is the part people skip and then get bitten by: coerce every schema to a root type: "object", ensure every name in required exists in properties, give every property node a type, and flatten anyOf/oneOf/allOf to a representative branch — or a strict client rejects the entire list on the first bad row. Verify with:
curl -s -X POST https://<host>/api/mcp -H "Authorization: Bearer $MCP_TOKEN" \
-H 'content-type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | python3 -c \
"import json,sys;print(len(json.load(sys.stdin)['result']['tools']))"Expected output: one integer, equal to the count of enabled, planner-visible rows.
Symptom, cause, fix
| Symptom | Cause | Fix |
|---|---|---|
| Client shows zero tools and no error | The whole tools/list was rejected on the first invalid schema; Moonshot and Kimi validate strictly | Normalise every schema: object root, every required name present in properties, a type on every node, no combinators. functions/api/mcp.js:44–78 |
401 unauthorized from /api/mcp | Bearer token mismatch | Send Authorization: Bearer <MCP_TOKEN> or the x-mcp-token header. The check is functions/api/mcp.js:23–28 |
| Tens of thousands of input tokens before the first user message | The client loads every definition at connect | Turn on the client's deferred tool loading, or move to a small surface |
| A new capability is invisible to the client | The client ignores notifications/tools/list_changed, or the server declares listChanged: false | Reconnect the client. The three filed reports above show reconnect is the reliable path |
A tool exists in the table but not in tools/list | The row has enabled = 0 or planner_visible = 0 | Intentional. planner_visible = 0 keeps a capability callable by key while off the tool surfaces |
| 150 items means 150 tool calls | Round trips happen between completions | Expose an HTTP path a code sandbox can loop over, or one tool that takes a batch |
| Prompt cache hit rate collapses after adding a server | Definitions sit at the head of the context, and changing them invalidates the cache | Keep the definition set fixed across a session; load per-task capabilities through a call, not a definition |
codex exec returns an empty turn | A configured server was deferred behind tool_search and never surfaced | openai/codex#24536. Pin the server as directly exposed until it closes |
The comparison against staying inside the schema paradigm entirely is Tool Search and catalogue-as-data.
Key evidence
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